Data processing method, device and equipment

Abstract

The embodiment of the invention discloses a data processing method, device and equipment, and the method comprises the steps: receiving a semantic obtaining request for target data, and the semantic obtaining request comprises semantic coding information and semantic input parameter information; obtaining semantic configuration information corresponding to the target data based on the semantic coding information, and initializing a semantic object logic attribute value corresponding to the target data based on the semantic input parameter information; calling a semantic calculation unit based on the semantic configuration information corresponding to the target data, and performing semantic calculation on the target data through the called semantic calculation unit based on the semantic configuration information corresponding to the target data and the initialized semantic object logic attribute value corresponding to the target data, a corresponding semantic calculation result is obtained; and based on semantic configuration information corresponding to the target data and the semantic calculation result, constructing and outputting semantic information of the target data.

Description

Technical Field

[0001] This document relates to the field of computer technology, and in particular to a data processing method, device and equipment. Background Art

[0002] As people pay more and more attention to their own arbitrary data, privacy protection has become one of the most concerned issues. Under the privacy protection business, the personal information ledger system of the privacy protection platform is positioned to collect various types of data and mark the data objects with feature labels according to business needs. However, in the usual development mode, for different business semantics, technical personnel are required to specially develop corresponding rule program codes and perform technical iterations. At the same time, different data objects need to be queried separately. The development workload is large, the development process is long, the iteration cycle is long, and it cannot be flexibly adjusted according to business needs. For this reason, it is necessary to provide a better business semantic construction mechanism, especially the construction of business semantics for data operations, so as to reduce the development workload and shorten the development process and iteration cycle. Summary of the invention

[0003] The purpose of the embodiments of this specification is to provide a better business semantics construction mechanism, especially the construction of business semantics for data operations, so as to provide fast, general and adjustable object data acquisition during business semantic calculations and support the configurable computing capabilities of business semantics.

[0004] In order to implement the above technical solution, the embodiments of this specification are implemented as follows: A data processing method provided by an embodiment of the present specification comprises: receiving a semantic acquisition request for target data, wherein the semantic acquisition request comprises semantic coding information and semantic input parameter information. Based on the semantic coding information, the semantic configuration information corresponding to the target data is acquired, and the logical attribute value of the semantic object corresponding to the target data is initialized based on the semantic input parameter information. Based on the semantic configuration information corresponding to the target data, a semantic calculation unit is called, and based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data, a semantic calculation is performed on the target data by the called semantic calculation unit to obtain a corresponding semantic calculation result. The semantic information of the target data is constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result.

[0005] An embodiment of the present specification provides a data processing device, the device includes a semantic computing interface, a semantic configuration module, a semantic logic context module and a semantic computing engine, wherein: the semantic computing interface is configured to receive a semantic acquisition request for target data, and the semantic acquisition request includes semantic coding information and semantic input parameter information. The semantic configuration module is configured to manage the configuration information of the logical semantic rules describing the target data, and is configured to obtain the semantic configuration information corresponding to the target data based on the semantic coding information. The semantic logic context module is configured to save and obtain the logical attribute values ​​of the semantic objects corresponding to the target data during the semantic computing process, and is configured to initialize the logical attribute values ​​of the semantic objects corresponding to the target data based on the semantic input parameter information. The semantic configuration module is configured to call the semantic computing unit in the semantic computing engine based on the semantic configuration information corresponding to the target data. The semantic computing engine is configured to perform semantic computing on the target data based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data by calling a semantic computing unit to obtain corresponding semantic computing results, and to construct and output the semantic information of the target data based on the semantic configuration information corresponding to the target data and the semantic computing results.

[0006] A data processing device is provided in an embodiment of the present specification, and the data processing device includes: a processor; and a memory arranged to store computer executable instructions, wherein the executable instructions, when executed, cause the processor to: receive a semantic acquisition request for target data, wherein the semantic acquisition request includes semantic coding information and semantic input parameter information. Based on the semantic coding information, the semantic configuration information corresponding to the target data is acquired, and the logical attribute value of the semantic object corresponding to the target data is initialized based on the semantic input parameter information. Based on the semantic configuration information corresponding to the target data, a semantic calculation unit is called, and based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data, the target data is semantically calculated by the called semantic calculation unit to obtain a corresponding semantic calculation result. The semantic information of the target data is constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result.

[0007] The embodiments of this specification also provide a storage medium, which is used to store computer-executable instructions. When the executable instructions are executed by a processor, they implement the following process: receiving a semantic acquisition request for target data, wherein the semantic acquisition request includes semantic coding information and semantic input parameter information. Based on the semantic coding information, semantic configuration information corresponding to the target data is acquired, and the logical attribute value of the semantic object corresponding to the target data is initialized based on the semantic input parameter information. Based on the semantic configuration information corresponding to the target data, a semantic calculation unit is called, and based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data, semantic calculation is performed on the target data by the called semantic calculation unit to obtain a corresponding semantic calculation result. The semantic information of the target data is constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result.

[0008] The embodiments of this specification also provide a computer program product, including a computer program, which implements the following process when executed by a processor: receiving a semantic acquisition request for target data, wherein the semantic acquisition request includes semantic coding information and semantic input parameter information. Based on the semantic coding information, the semantic configuration information corresponding to the target data is acquired, and the logical attribute value of the semantic object corresponding to the target data is initialized based on the semantic input parameter information. Based on the semantic configuration information corresponding to the target data, a semantic calculation unit is called, and based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data, the target data is semantically calculated by the called semantic calculation unit to obtain a corresponding semantic calculation result. The semantic information of the target data is constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the drawings required for use in the embodiments or the prior art description will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative labor. Figure 1 This is a schematic diagram of the structure of a data processing system in this specification; Figure 2 This is an embodiment of a data processing method of this specification; Figure 3 This is a schematic diagram of a page for obtaining semantic information in this manual; Figure 4 A schematic diagram of a data processing process of this specification; Figure 5 Another data processing method embodiment of this specification; Figure 6 A schematic diagram of another data processing process of this specification; Figure 7 This is another data processing method embodiment of the present specification; Figure 8 This is a schematic diagram of the processing process of a semantic logic context module in this specification; Fig. 9 This is another data processing method embodiment of the present specification; Fig.10 This is a schematic diagram of another data processing process of this specification; Fig.11 This is another data processing method embodiment of the present specification; Fig.12 This is a schematic diagram of the processing process of another semantic logic context module in this specification; Fig.13 A schematic diagram of a semantic computing process in this specification; Fig.14 A schematic diagram of the execution process of a semantic computing unit in this specification; Fig.15 This is a schematic diagram of the relationship between an application, interface, and link in this manual; Fig.16 This is another data processing method embodiment of the present specification; Fig.17 This is a schematic diagram of another data processing process of this specification; Fig.18 This is an embodiment of a data processing device of the present specification; Fig.19 Another data processing device embodiment of the present specification; Fig. 20 This is a structural diagram of another data processing system in this specification; Fig.21 This is an embodiment of a data processing device in this specification. DETAILED DESCRIPTION

[0010] The embodiments of this specification provide a data processing method, device and equipment.

[0011] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0012] The embodiments of this specification provide a business semantic construction mechanism for data operation. As people pay more and more attention to their own data, privacy protection has become one of the most concerned issues. Under the privacy protection business, the personal information account system of the privacy protection platform is positioned to collect various types of data and mark feature tags for the data objects according to business needs. However, in the usual development mode, such as Figure 1 As shown, for different business semantics, technicians need to develop corresponding rules program code and perform technical iterations. At the same time, different data objects need to be queried separately. The development workload is large, the development process is long, and the iteration cycle is long. Moreover, under this method, on the one hand, the calculation logic of business semantics is usually only expressed in the software program code, and the expression of business logic is not clear and direct enough, and it cannot be flexibly adjusted according to business needs; on the other hand, different semantic calculation programs consume data of different data objects repeatedly. When the data object adds or modifies attribute information, different semantic calculation programs need to modify the data consumption logic separately, so that the change has a large impact and a long modification cycle. For this reason, it is necessary to provide a better business semantic construction mechanism, especially for the construction of business semantics for data operations. The embodiment of this specification provides an achievable method. Through the configurable business semantic calculation rules, the structured logic modeling and rule description of business semantics are realized, so that the business semantic configuration process is digitized, and the research and development cycle of semantic customization development is shortened. Moreover, through one-stop management of different data object attribute information, it can provide fast, general, and adjustable object data acquisition during business semantic calculation, supporting the configurable computing capability of business semantics. For specific processing, please refer to the specific content in the following embodiment.

[0013] like Figure 2As shown, an embodiment of this specification provides a data processing method, and the execution subject of the method can be a terminal device or a server, etc., wherein the terminal device can be a mobile terminal device such as a mobile phone, a tablet computer, or a computer device such as a laptop or a desktop computer, or an IoT device (specifically such as a smart watch, a car-mounted device, etc.), etc., wherein the server can be an independent server, or a server cluster composed of multiple servers, etc., and the server can be a background server for financial services or online shopping services, or a background server for an application, etc. In this embodiment, the execution subject is taken as an example for detailed description. For the case where the execution subject is a terminal device, please refer to the following server situation processing, which will not be repeated here. The method can specifically include the following steps: In step S202, a semantic acquisition request for target data is received, where the semantic acquisition request includes semantic encoding information and semantic input parameter information.

[0014] Among them, the target data can be any data, for example, the target data can be the privacy data of a certain user, such as the user's identity information, the user's account information, etc. The target data can also be the data of a certain application, the target data can also be the data of a certain commodity, the target data can also be the transaction data between different users, the target data can also be the transaction data between different users and a certain merchant, etc., which can be set according to the actual situation. The semantic coding information can be the unique coding information used to identify the semantic information, and can be constructed in a variety of ways. For example, the semantic coding information can be composed of a number string composed of multiple numbers, or a letter string composed of multiple letters, or a character string composed of a combination of letters and numbers, such as SC00001, H5486ta, etc. In addition, it can also be composed of multiple other special characters, letters and numbers, which can be set according to the actual situation. The semantic input parameter information can be the information of the parameters that need to be transmitted set for the semantic information. The semantic input parameter information can include numerical values, text, etc., which can be set according to the actual situation, and the embodiments of this specification do not limit this.

[0015] In implementation, when it is necessary to determine the semantic information of certain data (i.e., target data), the corresponding page can be obtained through the terminal device, such as Figure 3As shown, the page may include an input box for semantic coding information and an input box for semantic input parameter information, as well as a confirmation button and a cancel button, etc. In addition, in addition to the above-mentioned input boxes and buttons, it may also include input boxes and / or buttons for other information, etc., which can be set specifically according to actual conditions. The technician can enter the corresponding semantic coding information and semantic input parameter information in the above-mentioned input box for semantic coding information and the input box for semantic input parameter information, respectively. After the input is completed, the confirmation button can be clicked. At this time, the terminal device can obtain the semantic coding information and semantic input parameter information entered by the technician. In addition, the terminal device can also obtain other relevant information, such as the identification of the target data, the application scenario information of the target data, etc., and can generate a semantic acquisition request for the target data based on the acquired information, and can send the semantic acquisition request to the server, and the server can receive the semantic acquisition request for the target data.

[0016] For example, a business system includes multiple platforms, such as a basic security platform, an intelligent interaction platform, a content security platform, etc. Each of these platforms contains corresponding applications, but does not include a privacy protection platform, and the current applications do not include applications with application labels as privacy protection platforms. If the target data is application A, and application A actually belongs to the application of the privacy protection platform, then it is necessary to label application A with an application label. In order to label application A with an application label, it is necessary to first determine the semantic information of application A. Based on this, the above page can be obtained through the terminal device. After the technician enters the corresponding semantic coding information and semantic input parameter information in the above page, he can click the OK button. The terminal device can obtain the semantic coding information and semantic input parameter information, and use this to generate a semantic acquisition request for application A. The semantic acquisition request can be sent to the server, and the server can receive the semantic acquisition request for application A.

[0017] In step S204, semantic configuration information corresponding to the target data is acquired based on the semantic coding information, and logical attribute values ​​of the semantic objects corresponding to the target data are initialized based on the semantic input parameter information.

[0018] Among them, the semantic configuration information can be a semantic rule pre-configured for the semantics of a specified business (such as a newly added business, etc.) or data, and the semantic configuration information is loaded during the semantic calculation process to perform the semantic calculation to obtain the corresponding result. The semantic configuration information may include a variety of different information or semantic rules. For example, the semantic configuration information may include one or more of semantic encoding information, semantic name, semantic type, input data configuration information, output data configuration information, call rules, etc., where the semantic name can be used to intuitively explain the text description of the meaning of the semantic business, such as privacy protection platform application identification, etc. The semantic type can include multiple types, such as data verification class, semantic object annotation class, etc., which can be set according to actual conditions. The input data configuration information can be used to standardize or unify the presentation form of the input data, the output data configuration information can be used to standardize or unify the presentation form of the output data, and the call rule can be a rule for scheduling specified data or execution units, etc., which can be shown in Table 1 below.

[0019] Table 1

[0020] In implementation, after receiving a semantic acquisition request for target data, the server can parse the semantic acquisition request, and can extract the semantic coding information and semantic input parameter information contained in the semantic acquisition request based on the parsing result. The corresponding semantic configuration information can be loaded according to the semantic coding information, and the loaded semantic configuration information can be used as the semantic configuration information corresponding to the target data. The logical attribute value of the semantic object corresponding to the target data can be initialized according to the semantic input parameter information to obtain the initialized logical attribute value of the semantic object corresponding to the target data.

[0021] In step S206, the semantic computing unit is called based on the semantic configuration information corresponding to the target data, and based on the semantic configuration information corresponding to the target data and the logical attribute value of the semantic object corresponding to the initialized target data, the target data is semantically computed by the called semantic computing unit to obtain a corresponding semantic computing result.

[0022] In implementation, since the semantic configuration information can be used to call the execution unit to execute the corresponding business, the specified semantic computing unit can be called through the semantic configuration information corresponding to the target data (or the specified information or calling rules in the semantic configuration information corresponding to the target data). The called semantic computing units may include one or more. If the called semantic computing units include multiple, the calling order of the multiple semantic computing units can also be set. In addition, if the multiple semantic computing units have a hierarchical structure, the calling order of the semantic computing units in each layer can be set, and the results obtained by the semantic computing units of the lower layer can be returned to the corresponding semantic computing units of the upper layer. The semantic computing units of the upper layer will then feed back the results they obtained upward until they reach the top-level semantic computing unit.

[0023] like Figure 4 As shown, the semantic object logical attribute value corresponding to the initialized target data can be analyzed to determine the semantic object logical attribute information corresponding to the target data, including the type of the semantic object corresponding to the target data, the logical attribute name, the logical attribute type, etc. Based on the semantic name, the semantic type, the configuration information of the input data, etc. in the semantic configuration information, as well as the semantic object logical attribute value and the semantic object logical attribute information, the target data can be semantically calculated by the called semantic calculation unit to obtain the corresponding semantic calculation result.

[0024] In step S208, semantic information of the target data is constructed and output based on the semantic configuration information and semantic calculation results corresponding to the target data.

[0025] In implementation, the semantic calculation result can be adjusted based on the configuration information of the output data in the semantic configuration information, and the semantic information of the target data that conforms to the configuration information of the output data can be constructed, and the semantic information of the target data can be output. Subsequently, the target data can be verified based on the semantic information of the target data, or the target data can be annotated with semantic objects based on the semantic information of the target data. For example, based on the above example, the semantic objects of the above application A can be annotated based on the semantic information of the target data, and finally application A can be annotated as an application of the privacy protection platform.

[0026] The embodiments of the present specification provide a data processing method, by, upon receiving a semantic acquisition request for target data, acquiring semantic configuration information corresponding to the target data based on the semantic coding information included in the semantic acquisition request, and initializing the semantic object logical attribute value corresponding to the target data based on the semantic input parameter information included in the semantic acquisition request, then, calling a semantic computing unit based on the semantic configuration information corresponding to the target data, and performing semantic computing on the target data based on the semantic configuration information corresponding to the target data and the initialized semantic object logical attribute value corresponding to the target data by the called semantic computing unit to obtain a corresponding semantic computing result, and finally, constructing and outputting the semantic information of the target data based on the semantic configuration information corresponding to the target data and the semantic computing result, in this way, by constructing the semantic configuration information and the semantic object logical attribute information, digitally modeling the business semantics, constructing the semantic computing unit, etc., the online structured configuration of business semantics and the data computing based on the semantic configuration rules in the complex business data operation scenarios are realized, which can improve the efficiency of data operation work, avoid repeated development work caused by changes in business rules, shorten the working time consumption of data operation, and reduce the R&D time of program development.

[0027] In practical applications, the specific processing methods for initializing the semantic object logical attribute value corresponding to the target data based on the semantic input parameter information in the above step S204 can be various. An optional processing method is provided below, such as Figure 5 As shown, please refer to the processing of the following steps S2042 and S2044 for details.

[0028] In step S2042, the semantic logical context corresponding to the target data is initialized based on the semantic input parameter information.

[0029] The semantic logic context can be used to initialize the logical attribute values ​​of the semantic objects required for the semantic computing process.

[0030] In implementation, Figure 6 As shown, semantic input parameter information can be extracted from the semantic acquisition request, and the semantic logical context corresponding to the target data can be initialized based on the semantic input parameter information to obtain an initialized semantic logical context.

[0031] In step S2044, a semantic logical context corresponding to the target data is created, and the semantic object logical attribute value corresponding to the target data is initialized according to the semantic input parameter information.

[0032] In implementation, Figure 6As shown, based on the above-mentioned initialized semantic logical context, a semantic logical context corresponding to the target data can be created, and the semantic object logical attribute value corresponding to the target data can be initialized according to the semantic input parameter information to obtain the semantic object logical attribute value corresponding to the initialized target data.

[0033] In practical applications, the above-mentioned semantic configuration information may include baseline semantic coding information. Based on this, the specific processing method for obtaining the semantic configuration information corresponding to the target data based on the semantic coding information in the above-mentioned step S204 can be varied. An optional processing method is provided below, which may specifically include the following contents: based on the semantic coding information, the semantic configuration information corresponding to the baseline semantic coding information matching the semantic coding information is obtained from multiple pre-stored semantic configuration information, and the obtained semantic configuration information is used as the semantic configuration information corresponding to the target data.

[0034] In implementation, the semantic configuration information may include semantic coding information, which may be reference semantic coding information. After the semantic coding information is extracted in the semantic acquisition request, the semantic coding information may be compared with the reference semantic coding information in the semantic configuration information. If the semantic coding information is the same as a reference semantic coding information, the semantic configuration information corresponding to the reference semantic coding information may be obtained, and the obtained semantic configuration information may be used as the semantic configuration information corresponding to the target data.

[0035] In actual applications, the above-mentioned semantic configuration information may include a semantic computing logic model. Based on this, the specific processing method for calling the semantic computing unit based on the semantic configuration information corresponding to the target data in the above-mentioned step S206 can be varied. An optional processing method is provided below, which may specifically include the following: extracting the semantic computing logic model from the semantic configuration information corresponding to the target data, and calling the semantic computing unit based on the extracted semantic computing logic model. The semantic computing logic model is used to maintain the logical configuration of the semantic computing, and the logical configuration includes one or more of the type of the semantic computing unit, the operator, the logical attribute information of the semantic object, the reference value, and the subsequent semantic computing unit set.

[0036] Among them, the semantic computing logic model is used to maintain the logical configuration of semantic computing and to schedule each semantic computing unit. The logical configuration includes one or more of the type of semantic computing unit, operator, semantic object logical attribute information, reference value, and subsequent semantic computing unit set, which can be shown in Table 2 below.

[0037] Table 2

[0038] The semantic computing logic model can be exemplified as follows: { type: and next:[ { / / Application data belongs to the special offline project feature including ${A} type: col operator: feature-any_in-features logicProp: bakApp.odsFeature config: ${A} }, { / / Application features do not contain ${B} type: col operator: !feature-any_in-features logicProp: bakApp.features config: ${B} } ] } In implementation, the semantic computing logic model can be extracted from the semantic configuration information corresponding to the target data. Since the semantic computing logic model has the function of scheduling each semantic computing unit, the semantic computing unit can be called based on the extracted semantic computing logic model. In addition, the semantic computing logic model can also maintain information such as the type, operator, semantic object logical attribute information, reference value, and subsequent semantic computing unit set of the semantic computing unit in the semantic computing process.

[0039] In practical applications, in the above step S206, based on the semantic configuration information corresponding to the target data and the semantic object logical attribute value corresponding to the initialized target data, the semantic calculation unit is called to perform semantic calculation on the target data to obtain the corresponding semantic calculation result. There are many specific processing methods. The following is an optional processing method, such as Figure 7 As shown, the processing may specifically include the following steps S2062 to S2066.

[0040] In step S2062, based on the initialized semantic object logical attribute value corresponding to the target data, it is queried whether the semantic object logical attribute value corresponding to the target data exists in the logical attribute cache.

[0041] In implementation, Figure 8As shown, a semantic logic context module can be set for obtaining the logical attribute information of the semantic object. The semantic logic context module can be used to save and obtain the logical attribute values ​​of the semantic object during the semantic calculation process, so as to decouple the semantic calculation process from the process of obtaining the logical attribute information of the semantic object. The semantic logic context module can include two parts: a logical attribute submodule for querying and saving the logical attribute values ​​of the semantic object and the logical attribute information of the semantic object, and an external data submodule for querying and saving external atomic data. Based on this, an object data model can also be set. The object data model can be used to maintain and manage the logical attribute information of the semantic object, and can be used to obtain the logical attribute information of the semantic object during the semantic calculation process. The object data model can also include an external data service, which can be a service identifier for calling an external database, and records the service information used for querying the logical attribute values ​​of the semantic object and the logical attribute information of the semantic object.

[0042] Based on the above architecture, the logical attribute submodule needs to query the logical attribute information of the semantic object during the semantic calculation process. At this time, the logical attribute submodule can query whether there is cached data in the logical attribute cache, and whether the cached data contains the logical attribute value of the semantic object corresponding to the target data.

[0043] The logical attribute cache can be stored in a secondary key-value pair format. The primary key-value pair key format is ${objectType}_${objectId}, which saves all logical attribute information of each semantic object. The secondary key-value pair key is the logical attribute value of the semantic object, which saves the logical attribute information of a semantic object. See the following example: { "bakApp_app1":{ "belongFeature":"aa", "ouCode":"bb" } "api_apiCodeA":{ "controlStatus":"1" } } In step S2064, if it exists, the semantic object logical attribute information corresponding to the target data is determined from the logical attribute cache based on the semantic object logical attribute value corresponding to the target data and the object data model, and based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data, the target data is semantically calculated by the called semantic calculation unit to obtain the corresponding semantic calculation result.

[0044] In implementation, Figure 8As shown, if the logical attribute value of the semantic object corresponding to the target data exists in the logical attribute cache, the logical attribute value of the semantic object corresponding to the target data can be analyzed from the logical attribute cache through the object data model to determine the logical attribute information of the semantic object corresponding to the target data. Then, based on the semantic configuration information corresponding to the target data and the logical attribute information of the semantic object corresponding to the target data, the semantic calculation unit called can be used to perform semantic calculation on the target data to obtain the corresponding semantic calculation result. The specific processing process can be referred to the aforementioned related content, which will not be repeated here.

[0045] In step S2066, if it does not exist, the external database is called according to the external data service configured in the object data model to obtain the semantic object logical attribute information corresponding to the target data, the semantic object logical attribute value corresponding to the target data and the acquired semantic object logical attribute information corresponding to the target data are stored in the logical attribute cache, and based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data, the target data is semantically calculated by the called semantic calculation unit to obtain the corresponding semantic calculation result.

[0046] In implementation, if the semantic object logical attribute value corresponding to the target data does not exist in the logical attribute cache, the external data service configured in the object data model can be obtained, and the external database of the external data submodule in the semantic logical context module can be called through the external data service, and the semantic object logical attribute information corresponding to the target data can be obtained from the external database, and the semantic object logical attribute value corresponding to the target data and the acquired semantic object logical attribute information corresponding to the target data can be stored in the logical attribute cache. Then, based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data, the target data can be semantically calculated by the called semantic calculation unit to obtain the corresponding semantic calculation result. The specific processing process can be referred to the aforementioned related content, which will not be repeated here.

[0047] In practical applications, the specific processing methods of calling the external database to obtain the semantic object logical attribute information corresponding to the target data according to the external data service configured in the object data model in the above step S2066 can be varied. The following is an optional processing method, such as Fig. 9 As shown, the processing may specifically include the following steps S206602 and S206604.

[0048] In step S206602, the external database is called according to the external data service configured in the object data model to obtain the target semantic object data that matches the semantic object logical attribute value corresponding to the target data.

[0049] In step S206604, the target semantic object data is converted into semantic object logical attribute information corresponding to the target data based on the logical attribute conversion rule configured in the object data model.

[0050] In implementation, Fig.10 As shown, considering that the data in the external database may be different from the local data (such as different formats, different description methods, etc.), a logical attribute conversion rule can be set in the object data model. The logical attribute conversion rule can be used to convert the data in the external database into data that meets local requirements. In practical applications, the logical attribute conversion rule can be a logical description for obtaining the logical attribute value of the semantic object from the query result obtained through the external data service (including the value path (wherein the value path can start with "$", that is, the logical attribute value of the semantic object is obtained from the query result obtained from the external data service) and the conversion method (the conversion method can use "@{}" to wrap the specific conversion method or conversion rule) etc.), if conversion is required, the logical attribute value of the semantic object obtained through the value path will be format converted. Based on this, the logical attribute conversion rule configured in the object data model can be used to convert the target semantic object data obtained through the value path to convert the target semantic object data into the semantic object logical attribute information corresponding to the target data.

[0051] In practical applications, the specific processing methods of calling the external database to obtain the semantic object logical attribute information corresponding to the target data according to the external data service configured in the object data model in the above step S2066 can be varied. The following is an optional processing method, such as Fig.11 As shown, the processing may specifically include the following steps S206606 to S206610.

[0052] In step S206606, the external database is called according to the external data service configured in the object data model, and it is queried whether there is a semantic object logical attribute value corresponding to the target data in the cache of the external database.

[0053] In implementation, Fig.12 As shown, the external database can be called according to the external data service configured in the object data model, and then, the cache of the external database can be first queried to see whether there is a semantic object logical attribute value corresponding to the target data.

[0054] The cache of the external database can be stored in a secondary key-value pair format. The primary key-value pair key format is ${server}_${objectId}, which saves the data information obtained by calling different external data services for each semantic object. The secondary key-value pair key is the logical attribute information of the data returned by the external data service, which saves the logical attribute information returned by calling the external data service. See the following example: { "bakAppQueryServerA_app1":{ "prop1":"cc", "prop2":"dd" } "apiQueryServerB_apiCodeA":{ "prop3":"ee" } } In step S206608, if it exists, the semantic object logical attribute information corresponding to the target data is obtained from the cache of the external database based on the semantic object logical attribute value corresponding to the target data.

[0055] In step S206610, if it does not exist, the semantic object logical attribute information corresponding to the target data is obtained from the external database based on the semantic object logical attribute value corresponding to the target data.

[0056] In implementation, Fig.12 As shown, if it does not exist, the semantic object logical attribute information corresponding to the target data is obtained from the external database based on the semantic object logical attribute value corresponding to the target data, and then the semantic object logical attribute value corresponding to the target data and the obtained semantic object logical attribute information corresponding to the target data can be correspondingly stored in the cache of the external database. In addition, the semantic object logical attribute value corresponding to the target data and the obtained semantic object logical attribute information corresponding to the target data can also be correspondingly stored in the logical attribute cache, etc.

[0057] In practical applications, the above-mentioned semantic computing logic model is used to maintain the logical configuration of semantic computing, and the logical configuration includes operators and reference values. Based on this, the above-mentioned semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data are used to perform semantic computing on the target data through the called semantic computing unit. The specific processing methods for obtaining the corresponding semantic computing results can be various. The following is an optional processing method, such as Fig.13 As shown, the processing may specifically include the following steps A2 to A6.

[0058] In step A2, the reference value is obtained from a preset reference value set based on the semantic computing logic model in the semantic configuration information corresponding to the target data.

[0059] The reference value may be pre-saved in a reference value set when the semantic configuration information is defined, and the storage format may be key=reference value code, value=reference value, etc.

[0060] In step A4, operator information for performing semantic calculation is acquired based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data.

[0061] The operator information may include multiple types, such as addition operator, subtraction operator, multiplication operator, division operator, logical AND operator, logical OR operator, etc., which can be set according to actual conditions. The operator in this embodiment can be a function for semantic calculation, the input data of the function is the semantic object logical attribute information and reference value, the output data is the semantic calculation result, the operator format can be: semantic calculation result = (semantic object logical attribute information) operator (reference value), the returned result is true or false, for example, as shown in Table 3 below Table 3

[0062] In step A6, the semantic calculation unit is called, with the semantic object logical attribute information corresponding to the target data and the obtained reference value as input data, and the obtained operator is used to perform semantic calculation to determine the semantic calculation result for the target data.

[0063] In actual applications, the semantic computing unit may include a computing class semantic computing unit and a merging class semantic computing unit. Based on this, if the semantic computing unit is a computing class semantic computing unit, the specific processing methods of the above step A6 can be varied. An optional processing method is provided below, which may specifically include the following: by calling the computing class semantic computing unit, taking the semantic object logical attribute information corresponding to the target data and the obtained reference value as input data, using the obtained operator to perform semantic calculations, and obtaining the semantic calculation result corresponding to the computing class semantic computing unit, and returning the semantic calculation result corresponding to the computing class semantic computing unit to the semantic computing unit of the upper level of the computing class semantic computing unit to determine the semantic calculation result for the target data.

[0064] In implementation, Fig.14As shown, after the called computing class semantic calculation unit performs semantic calculation to obtain the corresponding semantic calculation result, the semantic calculation result corresponding to the computing class semantic calculation unit can be returned to the upper-level semantic calculation unit of the computing class semantic calculation unit. If the upper-level semantic calculation unit is still a computing class semantic calculation unit, it can be executed based on the above processing, that is, using the semantic object logical attribute information corresponding to the target data and the obtained reference value as input data, using the obtained operator to perform semantic calculation to obtain the corresponding semantic calculation result, and returning the obtained semantic calculation result to the upper-level semantic calculation unit. If the upper-level semantic calculation unit is a merging class semantic calculation unit, the following steps A62 and A64 can be executed.

[0065] If the semantic computing unit is a merge-type semantic computing unit, the specific processing methods of the above step A6 can be varied. An optional processing method is provided below, which can specifically include the processing of the following steps A62 and A64.

[0066] In step A62, the output data of the next-level semantic computing unit of the called merging-type semantic computing unit is obtained through the called merging-type semantic computing unit.

[0067] In step A64, the acquired output data is merged to obtain a merged result of the merged semantic calculation unit, and the merged result of the merged semantic calculation unit is returned to the upper-level semantic calculation unit of the merged semantic calculation unit to determine the semantic calculation result for the target data.

[0068] In implementation, Fig.14 As shown, after the merge-class semantic calculation unit obtains the merged result through the processing of step A62 and step A64, the merged result can be returned to the semantic calculation unit of the upper level of the merge-class semantic calculation unit. If the upper level semantic calculation unit is a calculation-class semantic calculation unit, the semantic object logical attribute information corresponding to the target data and the merged result can be used as input data, and the obtained operator can be used to perform semantic calculation to obtain the corresponding semantic calculation result, and the obtained semantic calculation result can be returned to the upper level semantic calculation unit. If the upper level semantic calculation unit is still a merge-class semantic calculation unit, the above-mentioned steps A62 and A64 can be executed until the highest level is reached, and finally the semantic calculation result for the target data can be obtained.

[0069] In actual applications, the object data model also includes one or more of the object type, logical attribute identifier and attribute type. The object type includes application, interface and link. The attribute type includes value type and object type. The value type includes text and feature list. The object type includes application and interface.

[0070] Among them, the object type is used to describe the type of the semantic object, which may include backend application bakApp, interface api, and link trFlow, etc. The logical attribute identifier is the unique identifier of the logical attribute information of the semantic object. In actual applications, its format can be as follows: the object type and the attribute name are concatenated with ".". The attribute type is used to distinguish the different types of the logical attribute values ​​of the semantic object. The attribute type may include value type and object type. The value type may include text and feature list, etc. The object type may include backend application and interface, etc. For details, please refer to the following Table 4.

[0071] Table 4

[0072] The relationship diagram of the data object model can be shown as Fig.15 As shown, the application includes the application name (i.e., AppName), subject, data ownership, and feature tags, etc.; the interface may include the interface name (i.e., InterfaceName), application name (i.e., AppName), management status, and feature tags, etc.; the link may include the request application name (i.e., ReqAppName), response application name (i.e., RespAppName), interface name (i.e., InterfaceName), and feature tags, etc.

[0073] The attribute information of the application may be shown in Table 5 below.

[0074] Table 5

[0075] The attribute information of the interface may be shown in Table 6 below.

[0076] Table 6

[0077] The attribute information of the link may be shown in Table 7 below.

[0078] Table 7

[0079] In practical applications, the specific processing methods of the above step S208 can be varied. An optional processing method is provided below, such as Fig.16 As shown, the processing may specifically include the following steps S2082 and S2084.

[0080] In step S2082, an output option set and semantic type information are extracted from the semantic configuration information corresponding to the target data, the output option set is used to output the output value specified by the semantic output of the output type, and the semantic type information is used to distinguish the type of the semantic calculation result.

[0081] In step S2084, semantic information of the target data is constructed and output based on the output option set, the semantic type information and the semantic calculation result.

[0082] In practical applications, the semantic information of the target data obtained in the above manner can be further applied to data verification or labeling of semantic objects. For details, please refer to the following contents: based on the semantic information of the target data, data verification is performed on the target data or the semantic object corresponding to the target data to obtain the corresponding verification result; or, based on the semantic information of the target data, labeling is performed on the semantic object corresponding to the target data to obtain the labeling information of the semantic object corresponding to the target data.

[0083] In practical applications, the above target data may be data related to data operations under privacy protection services.

[0084] The following describes in detail a data processing method provided by the embodiment of this specification in combination with a specific application scenario. Fig.17 As shown, the semantic object corresponding to the target data is a backend application, and the purpose of determining the semantic information corresponding to the target data is to mark the backend application. First, the business semantic definition can be performed, that is, the semantic object is determined to be a backend application. Then, the business semantic structure can be parsed through the above processing process to determine the logical attribute information involved in the semantic object (that is, the semantic object logical attribute information), which can specifically include two types of logical attribute information, namely, the application data attribution label and the application privacy feature label. After that, the semantic configuration information can be determined, which can include condition 1: the application data attribution label is within the scope of "privacy protection data identification"; condition 2: the application privacy feature label is not within the scope of "privacy protection". The semantic information corresponding to the backend application can be determined based on the core information and additional information in the object data model as data support, and the semantic configuration information can be used to determine. Finally, an application label can be set for the backend application based on the determined semantic information. The information in the application label is the privacy protection platform, thereby completing the labeling of the backend application.

[0085] The embodiments of the present specification provide a data processing method, by, upon receiving a semantic acquisition request for target data, acquiring semantic configuration information corresponding to the target data based on the semantic coding information included in the semantic acquisition request, and initializing the semantic object logical attribute value corresponding to the target data based on the semantic input parameter information included in the semantic acquisition request, then, calling a semantic computing unit based on the semantic configuration information corresponding to the target data, and performing semantic computing on the target data based on the semantic configuration information corresponding to the target data and the initialized semantic object logical attribute value corresponding to the target data by the called semantic computing unit to obtain a corresponding semantic computing result, and finally, constructing and outputting the semantic information of the target data based on the semantic configuration information corresponding to the target data and the semantic computing result, in this way, by constructing the semantic configuration information and the semantic object logical attribute information, digitally modeling the business semantics, constructing the semantic computing unit, etc., the online structured configuration of business semantics and the data computing based on the semantic configuration rules in the complex business data operation scenarios are realized, which can improve the efficiency of data operation work, avoid repeated development work caused by changes in business rules, shorten the working time consumption of data operation, and reduce the R&D time of program development.

[0086] In addition, an object data model is constructed to uniformly manage the object data model and the logical attribute information of semantic objects. The consumption and change of semantic objects do not require multiple maintenance. Moreover, the business semantics is logically modeled and described by rules using structured semantic configuration information. The semantic configuration process is digitized, the rule logic is clear and intuitive, and the business semantics calculates the semantic results based on the semantic computing unit. Based on the unified object data model, the semantic results are calculated for different semantic configuration information. Furthermore, this solution implements the management of configurable and computable business semantic computing rules, and decouples the object attribute acquisition from the semantic computing through the semantic logic context management. In addition, through the management of configurable business semantic computing rules, the structured logical modeling and rule description of business semantics are realized, making the business semantic configuration process digital and shortening the research and development cycle of semantic customization development. Moreover, through the semantic logic context management and the constructed unified object data model, the logical attribute information and data query services of different semantic objects are managed in one stop, which can provide fast, general and adjustable information acquisition in business semantic computing and support the configurable computing capability of business semantics.

[0087] The above is a data processing method provided in the embodiment of this specification. Based on the same idea, the embodiment of this specification also provides a data processing device, such as Fig.18 shown.

[0088] The data processing device comprises: a semantic computing interface, a semantic configuration module, a semantic logic context module and a semantic computing engine, wherein: The semantic computing interface is configured to receive a semantic acquisition request for target data, wherein the semantic acquisition request includes semantic encoding information and semantic input parameter information; The semantic configuration module is configured to manage configuration information describing the logical semantic rules of the target data, and is configured to obtain semantic configuration information corresponding to the target data based on the semantic encoding information; The semantic logic context module is configured to save and obtain the semantic object logic attribute value corresponding to the target data during the semantic calculation process, and is configured to initialize the semantic object logic attribute value corresponding to the target data based on the semantic input parameter information; The semantic configuration module is configured to call the semantic computing unit in the semantic computing engine based on the semantic configuration information corresponding to the target data; The semantic computing engine is configured to perform semantic computing on the target data based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data by calling a semantic computing unit to obtain corresponding semantic computing results, and to construct and output the semantic information of the target data based on the semantic configuration information corresponding to the target data and the semantic computing results.

[0089] In the embodiments of this specification, Fig.19 As shown, the apparatus further includes an object data model configured to maintain and manage logical attribute information of semantic objects; The semantic logic context module includes a logic attribute submodule and an external data submodule, wherein: The logical attribute submodule is configured to query whether the logical attribute value of the semantic object corresponding to the target data exists in the logical attribute cache based on the initialized logical attribute value of the semantic object corresponding to the target data; if it exists, determine the logical attribute information of the semantic object corresponding to the target data from the logical attribute cache based on the logical attribute value of the semantic object corresponding to the target data and according to the object data model; The external data submodule is configured to, if it does not exist, call an external database according to the external data service configured in the object data model to obtain the semantic object logical attribute information corresponding to the target data, and store the semantic object logical attribute value corresponding to the target data and the obtained semantic object logical attribute information corresponding to the target data in the logical attribute cache; The semantic computing engine is configured to perform semantic computing on the target data based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data by calling the semantic computing unit to obtain the corresponding semantic computing result.

[0090] In implementation, Fig. 20 As shown, the object data model may include links, interfaces and applications, wherein the links include request application identifiers, response application identifiers, interface names, feature tags and other related information, etc., the interfaces may include application identifiers, interface names, feature tags and other related information, etc., the applications may include application identifiers, feature tags and other related information, etc., and the object data model may provide data support for the semantic computing engine. In addition, it may also include multiple different semantic configuration information, including semantic configuration information 1, semantic configuration information 2, semantic configuration information 3…, and may also include processing mechanisms such as semantic configuration parsing, and may provide rule descriptions for the semantic computing engine through multiple different semantic configuration information. At the same time, semantic acquisition requests corresponding to different business semantics (which may include business semantics 1, business semantics 2, business semantics 3…) may also be received through the semantic computing interface.

[0091] In an embodiment of the present specification, the semantic logical context module is configured to initialize the semantic logical context corresponding to the target data based on the semantic input parameter information; create a semantic logical context corresponding to the target data, and initialize the semantic object logical attribute value corresponding to the target data according to the semantic input parameter information.

[0092] In the embodiment of the present specification, the semantic configuration module is configured to obtain, based on the semantic coding information, semantic configuration information corresponding to the reference semantic coding information matching the semantic coding information from a plurality of pre-stored semantic configuration information, and use the obtained semantic configuration information as the semantic configuration information corresponding to the target data; The semantic configuration module is configured to extract a semantic computing logic model from the semantic configuration information corresponding to the target data, and call a semantic computing unit based on the extracted semantic computing logic model. The semantic computing logic model is used to maintain the logical configuration of semantic computing, and the logical configuration includes one or more of the type of the semantic computing unit, the operator, the logical attribute information of the semantic object, the reference value, and the set of subsequent semantic computing units.

[0093] In the embodiment of the present specification, the external data submodule is configured to call an external database according to the external data service configured in the object data model to obtain target semantic object data that matches the semantic object logical attribute value corresponding to the target data; The logic attribute submodule is configured to convert the target semantic object data into semantic object logic attribute information corresponding to the target data based on the logic attribute conversion rule configured in the object data model.

[0094] In an embodiment of the present specification, the external data submodule is configured to call an external database according to the external data service configured in the object data model, and query whether the semantic object logical attribute value corresponding to the target data exists in the cache of the external database; if so, the semantic object logical attribute information corresponding to the target data is obtained from the cache of the external database based on the semantic object logical attribute value corresponding to the target data; if not, the semantic object logical attribute information corresponding to the target data is obtained from the external database based on the semantic object logical attribute value corresponding to the target data.

[0095] In an embodiment of the present specification, the semantic computing engine is configured to obtain the reference value from a preset reference value set based on the semantic computing logic model in the semantic configuration information corresponding to the target data; obtain operator information for performing semantic computing based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data; and determine the semantic computing result for the target data by performing semantic computing using the acquired operator and the semantic object logical attribute information corresponding to the target data and the acquired reference value as input data through the called semantic computing unit.

[0096] In the embodiment of this specification, the semantic computing unit includes a computing semantic computing unit and a merging semantic computing unit. If the semantic computing unit is a computing-type semantic computing unit, the semantic computing engine is configured to perform semantic computing by calling the computing-type semantic computing unit, taking the semantic object logical attribute information corresponding to the target data and the obtained reference value as input data, using the obtained operator to obtain the semantic computing result corresponding to the computing-type semantic computing unit, and returning the semantic computing result corresponding to the computing-type semantic computing unit to the semantic computing unit at the previous level of the computing-type semantic computing unit to determine the semantic computing result for the target data; If the semantic computing unit is a merging-type semantic computing unit, the semantic computing engine is configured to obtain the output data of the next-level semantic computing unit of the called merging-type semantic computing unit through the called merging-type semantic computing unit; merge the obtained output data to obtain the merged result of the merging-type semantic computing unit, and return the merged result of the merging-type semantic computing unit to the previous-level semantic computing unit of the merging-type semantic computing unit to determine the semantic computing result for the target data.

[0097] In an embodiment of the present specification, the object data model also includes one or more of an object type, a logical attribute identifier, and an attribute type, the object type includes an application, an interface, and a link, the attribute type includes a value type and an object type, the value type includes text and a feature list, and the object type includes an application and an interface.

[0098] In an embodiment of the present specification, the semantic computing engine is configured to extract an output option set and semantic type information from the semantic configuration information corresponding to the target data, the output option set being used to output a specified output value of the semantic output of the output type, and the semantic type information being used to distinguish the type of the semantic computing result; and construct and output the semantic information of the target data based on the output option set, the semantic type information and the semantic computing result.

[0099] In the embodiment of this specification, the device further includes: A verification module is configured to perform data verification processing on the target data or a semantic object corresponding to the target data based on the semantic information of the target data to obtain a corresponding verification result; The labeling module is configured to label the semantic object corresponding to the target data based on the semantic information of the target data to obtain the labeling information of the semantic object corresponding to the target data.

[0100] In the embodiments of this specification, the target data is data related to data operation under the privacy protection service.

[0101] For the specific processing procedures involved in the above-mentioned semantic computing interface, semantic configuration module, semantic logic context module, semantic computing engine, object data model, etc., please refer to the aforementioned related content and will not be repeated here.

[0102] The embodiments of the present specification provide a data processing device, which obtains semantic configuration information corresponding to the target data based on the semantic coding information included in the semantic acquisition request when receiving a semantic acquisition request for the target data, and initializes the semantic object logical attribute value corresponding to the target data based on the semantic input parameter information included in the semantic acquisition request. Then, a semantic calculation unit can be called based on the semantic configuration information corresponding to the target data, and based on the semantic configuration information corresponding to the target data and the initialized semantic object logical attribute value corresponding to the target data, semantic calculation is performed on the target data by the called semantic calculation unit to obtain a corresponding semantic calculation result. Finally, the semantic information of the target data can be constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result. In this way, by constructing the semantic configuration information and the semantic object logical attribute information, digital modeling of the business semantics, construction of the semantic calculation unit, etc., the online structured configuration of business semantics and data calculation based on semantic configuration rules in complex business data operation scenarios are realized, which can improve the efficiency of data operation work, avoid repeated development work caused by changes in business rules, shorten the working time consumption of data operation, and reduce the R&D time of program development.

[0103] In addition, an object data model is constructed to uniformly manage the object data model and the logical attribute information of semantic objects. The consumption and change of semantic objects do not require multiple maintenance. Moreover, the business semantics is logically modeled and described by rules using structured semantic configuration information. The semantic configuration process is digitized, the rule logic is clear and intuitive, and the business semantics calculates the semantic results based on the semantic computing unit. Based on the unified object data model, the semantic results are calculated for different semantic configuration information. Furthermore, this solution implements the management of configurable and computable business semantic computing rules, and decouples the object attribute acquisition from the semantic computing through the semantic logic context management. In addition, through the management of configurable business semantic computing rules, the structured logical modeling and rule description of business semantics are realized, making the business semantic configuration process digital and shortening the research and development cycle of semantic customization development. Moreover, through the semantic logic context management and the constructed unified object data model, the logical attribute information and data query services of different semantic objects are managed in one stop, which can provide fast, general and adjustable information acquisition in business semantic computing and support the configurable computing capability of business semantics.

[0104] The above is a data processing device provided in the embodiment of this specification. Based on the same idea, the embodiment of this specification also provides a data processing device, such as Fig.21 shown.

[0105] The data processing device may provide a terminal device or a server, etc. for the above embodiments.

[0106] The data processing device may have relatively large differences due to different configurations or performances, and may include one or more processors 2101 and memory 2102, and the memory 2102 may store one or more storage applications or data. Among them, the memory 2102 may be a short-term storage or a persistent storage. The application stored in the memory 2102 may include one or more modules (not shown in the figure), and each module may include a series of computer executable instructions in the data processing device. Furthermore, the processor 2101 may be configured to communicate with the memory 2102, and execute a series of computer executable instructions in the memory 2102 on the data processing device. The data processing device may also include one or more power supplies 2103, one or more wired or wireless network interfaces 2104, one or more input and output interfaces 2105, and one or more keyboards 2106.

[0107] Specifically in this embodiment, the data processing device includes a memory and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may include one or more modules, and each module may include a series of computer executable instructions in the data processing device, and the one or more programs are configured to be executed by one or more processors, including computer executable instructions for performing the following: Receiving a semantic acquisition request for target data, wherein the semantic acquisition request includes semantic encoding information and semantic input parameter information; Acquire semantic configuration information corresponding to the target data based on the semantic encoding information, and initialize logical attribute values ​​of the semantic object corresponding to the target data based on the semantic input parameter information; Based on the semantic configuration information corresponding to the target data, a semantic calculation unit is called, and based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data, the called semantic calculation unit performs semantic calculation on the target data to obtain a corresponding semantic calculation result; The semantic information of the target data is constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result.

[0108] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the data processing device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0109] The embodiments of the present specification provide a data processing device, which obtains semantic configuration information corresponding to the target data based on the semantic coding information included in the semantic acquisition request when receiving a semantic acquisition request for the target data, and initializes the semantic object logical attribute value corresponding to the target data based on the semantic input parameter information included in the semantic acquisition request. Then, a semantic calculation unit can be called based on the semantic configuration information corresponding to the target data, and based on the semantic configuration information corresponding to the target data and the initialized semantic object logical attribute value corresponding to the target data, semantic calculation is performed on the target data by the called semantic calculation unit to obtain a corresponding semantic calculation result. Finally, the semantic information of the target data can be constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result. In this way, by constructing the semantic configuration information and the semantic object logical attribute information, digital modeling of the business semantics, construction of the semantic calculation unit, etc., the online structured configuration of business semantics and data calculation based on semantic configuration rules in complex business data operation scenarios are realized, which can improve the efficiency of data operation work, avoid repeated development work caused by changes in business rules, shorten the working time consumption of data operation, and reduce the R&D time of program development.

[0110] In addition, an object data model is constructed to uniformly manage the object data model and the logical attribute information of semantic objects. The consumption and change of semantic objects do not require multiple maintenance. Moreover, the business semantics is logically modeled and described by rules using structured semantic configuration information. The semantic configuration process is digitized, the rule logic is clear and intuitive, and the business semantics calculates the semantic results based on the semantic computing unit. Based on the unified object data model, the semantic results are calculated for different semantic configuration information. Furthermore, this solution implements the management of configurable and computable business semantic computing rules, and decouples the object attribute acquisition from the semantic computing through the semantic logic context management. In addition, through the management of configurable business semantic computing rules, the structured logical modeling and rule description of business semantics are realized, making the business semantic configuration process digital and shortening the research and development cycle of semantic customization development. Moreover, through the semantic logic context management and the constructed unified object data model, the logical attribute information and data query services of different semantic objects are managed in one stop, which can provide fast, general and adjustable information acquisition in business semantic computing and support the configurable computing capability of business semantics.

[0111] Furthermore, based on the above Figures 2 to 16 In one embodiment, the present specification further provides a storage medium for storing computer executable instruction information. In a specific embodiment, the storage medium may be a USB flash drive, an optical disk, a hard disk, etc. When the computer executable instruction information stored in the storage medium is executed by the processor, the following process can be implemented: Receiving a semantic acquisition request for target data, wherein the semantic acquisition request includes semantic encoding information and semantic input parameter information; Acquire semantic configuration information corresponding to the target data based on the semantic encoding information, and initialize logical attribute values ​​of the semantic object corresponding to the target data based on the semantic input parameter information; Based on the semantic configuration information corresponding to the target data, a semantic calculation unit is called, and based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data, the called semantic calculation unit performs semantic calculation on the target data to obtain a corresponding semantic calculation result; The semantic information of the target data is constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result.

[0112] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the above-mentioned storage medium embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0113] The embodiment of the present specification provides a storage medium, which obtains the semantic configuration information corresponding to the target data based on the semantic coding information included in the semantic acquisition request when receiving a semantic acquisition request for the target data, and initializes the semantic object logical attribute value corresponding to the target data based on the semantic input parameter information included in the semantic acquisition request. Then, the semantic calculation unit can be called based on the semantic configuration information corresponding to the target data, and based on the semantic configuration information corresponding to the target data and the initialized semantic object logical attribute value corresponding to the target data, the target data is semantically calculated by the called semantic calculation unit to obtain a corresponding semantic calculation result. Finally, the semantic information of the target data can be constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result. In this way, by constructing the semantic configuration information and the semantic object logical attribute information, the business semantics are digitally modeled, the semantic calculation unit is constructed, etc., so that the online structured configuration of business semantics and the data calculation based on the semantic configuration rules in the complex business data operation scenario are realized, which can improve the efficiency of data operation work, avoid the repeated development work caused by the change of business rules, shorten the working time consumption of data operation, and reduce the R&D time of program development.

[0114] In addition, an object data model is constructed to uniformly manage the object data model and the logical attribute information of semantic objects. The consumption and change of semantic objects do not require multiple maintenance. Moreover, the business semantics is logically modeled and described by rules using structured semantic configuration information. The semantic configuration process is digitized, the rule logic is clear and intuitive, and the business semantics calculates the semantic results based on the semantic computing unit. Based on the unified object data model, the semantic results are calculated for different semantic configuration information. Furthermore, this solution implements the management of configurable and computable business semantic computing rules, and decouples the object attribute acquisition from the semantic computing through the semantic logic context management. In addition, through the management of configurable business semantic computing rules, the structured logical modeling and rule description of business semantics are realized, making the business semantic configuration process digital and shortening the research and development cycle of semantic customization development. Moreover, through the semantic logic context management and the constructed unified object data model, the logical attribute information and data query services of different semantic objects are managed in one stop, which can provide fast, general and adjustable information acquisition in business semantic computing and support the configurable computing capability of business semantics.

[0115] Furthermore, based on the above Figures 2 to 16 In one or more embodiments of the present specification, a computer program product is provided, including a computer program. When the computer program in the computer program product is executed by a processor, the following process can be implemented: Receiving a semantic acquisition request for target data, wherein the semantic acquisition request includes semantic encoding information and semantic input parameter information; Acquire semantic configuration information corresponding to the target data based on the semantic encoding information, and initialize logical attribute values ​​of the semantic object corresponding to the target data based on the semantic input parameter information; Based on the semantic configuration information corresponding to the target data, a semantic calculation unit is called, and based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data, the called semantic calculation unit performs semantic calculation on the target data to obtain a corresponding semantic calculation result; The semantic information of the target data is constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result.

[0116] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the above-mentioned computer program product embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0117] The embodiments of the present specification provide a computer program product, which obtains semantic configuration information corresponding to the target data based on the semantic coding information included in the semantic acquisition request when receiving a semantic acquisition request for the target data, and initializes the semantic object logical attribute value corresponding to the target data based on the semantic input parameter information included in the semantic acquisition request. Then, a semantic calculation unit can be called based on the semantic configuration information corresponding to the target data, and based on the semantic configuration information corresponding to the target data and the initialized semantic object logical attribute value corresponding to the target data, the target data is semantically calculated by the called semantic calculation unit to obtain a corresponding semantic calculation result. Finally, the semantic information of the target data can be constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result. In this way, by constructing the semantic configuration information and the semantic object logical attribute information, digital modeling of the business semantics, constructing the semantic calculation unit, etc., the online structured configuration of business semantics and data calculation based on semantic configuration rules in complex business data operation scenarios are realized, which can improve the efficiency of data operation work, avoid repeated development work caused by changes in business rules, shorten the working time consumption of data operation, and reduce the R&D time of program development.

[0118] In addition, an object data model is constructed to uniformly manage the object data model and the logical attribute information of semantic objects. The consumption and change of semantic objects do not require multiple maintenance. Moreover, the business semantics is logically modeled and described by rules using structured semantic configuration information. The semantic configuration process is digitized, the rule logic is clear and intuitive, and the business semantics calculates the semantic results based on the semantic computing unit. Based on the unified object data model, the semantic results are calculated for different semantic configuration information. Furthermore, this solution implements the management of configurable and computable business semantic computing rules, and decouples the object attribute acquisition from the semantic computing through the semantic logic context management. In addition, through the management of configurable business semantic computing rules, the structured logical modeling and rule description of business semantics are realized, making the business semantic configuration process digital and shortening the research and development cycle of semantic customization development. Moreover, through the semantic logic context management and the constructed unified object data model, the logical attribute information and data query services of different semantic objects are managed in one stop, which can provide fast, general and adjustable information acquisition in business semantic computing and support the configurable computing capability of business semantics.

[0119] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0120] In the 1990s, it was very clear whether the improvement of a technology was hardware improvement (for example, improvement of the circuit structure of diodes, transistors, switches, etc.) or software improvement (improvement of the method flow). However, with the development of technology, many improvements of the method flow today can be regarded as direct improvements of the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented with a hardware entity module. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming themselves, without having to ask chip manufacturers to design and make dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one kind of HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0121] The controller may be implemented in any suitable manner, for example, the controller may take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (e.g., software or firmware) executable by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, and the memory controller may also be implemented as part of the control logic of the memory. It is also known to those skilled in the art that, in addition to implementing the controller in a purely computer-readable program code manner, the controller may be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, such a controller may be considered as a hardware component, and the devices for implementing various functions included therein may also be considered as structures within the hardware component. Or even, the devices for implementing various functions may be considered as both software modules for implementing the method and structures within the hardware component.

[0122] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0123] For the convenience of description, the above devices are described in terms of functions and are divided into various units. Of course, when implementing one or more embodiments of this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0124] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, one or more embodiments of this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, one or more embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0125] The embodiments of this specification are described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable fraud case serial and parallel device to produce a machine, so that the instructions executed by the processor of the computer or other programmable fraud case serial and parallel device generate instructions for implementing the processes in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0126] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable fraud case serial and parallel device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0127] These computer program instructions may also be loaded onto a computer or other programmable device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0128] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0129] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0130] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined in this article, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0131] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0132] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, one or more embodiments of this specification may be in the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Furthermore, one or more embodiments of this specification may be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0133] One or more embodiments of the present specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. One or more embodiments of the present specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0134] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0135] The above description is only an embodiment of this specification and is not intended to limit this document. For those skilled in the art, this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this specification should be included in the scope of the claims of this specification.

Claims

1. A data processing method, the method comprising: Receiving a semantic acquisition request for target data, wherein the semantic acquisition request includes semantic encoding information and semantic input parameter information; Acquire semantic configuration information corresponding to the target data based on the semantic encoding information, and initialize logical attribute values ​​of the semantic object corresponding to the target data based on the semantic input parameter information; Based on the semantic configuration information corresponding to the target data, a semantic calculation unit is called, and based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data, the called semantic calculation unit performs semantic calculation on the target data to obtain a corresponding semantic calculation result; The semantic information of the target data is constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result.

2. According to the method of claim 1, the initializing the semantic object logical attribute value corresponding to the target data based on the semantic input parameter information comprises: Initialize the semantic logic context corresponding to the target data based on the semantic input parameter information; A semantic logical context corresponding to the target data is created, and a semantic object logical attribute value corresponding to the target data is initialized according to the semantic input parameter information.

3. According to the method of claim 2, the semantic configuration information includes reference semantic coding information and a semantic computing logic model, and the step of obtaining the semantic configuration information corresponding to the target data based on the semantic coding information includes: Based on the semantic coding information, semantic configuration information corresponding to reference semantic coding information matching the semantic coding information is obtained from a plurality of pre-stored semantic configuration information, and the obtained semantic configuration information is used as the semantic configuration information corresponding to the target data; The calling of the semantic computing unit based on the semantic configuration information corresponding to the target data includes: A semantic computing logic model is extracted from the semantic configuration information corresponding to the target data, and a semantic computing unit is called based on the extracted semantic computing logic model. The semantic computing logic model is used to maintain the logical configuration of semantic computing, and the logical configuration includes one or more of the type of the semantic computing unit, the operator, the logical attribute information of the semantic object, the reference value, and the set of subsequent semantic computing units.

4. The method according to claim 3, wherein based on the semantic configuration information corresponding to the target data and the initialized semantic object logical attribute value corresponding to the target data, the semantic calculation unit is called to perform semantic calculation on the target data to obtain the corresponding semantic calculation result, including: Based on the initialized logical attribute value of the semantic object corresponding to the target data, query whether the logical attribute value of the semantic object corresponding to the target data exists in the logical attribute cache; If it exists, then determine the semantic object logical attribute information corresponding to the target data from the logical attribute cache based on the semantic object logical attribute value corresponding to the target data and according to the object data model, and perform semantic calculation on the target data through the called semantic calculation unit based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data to obtain a corresponding semantic calculation result; If it does not exist, then according to the external data service configured in the object data model, an external database is called to obtain the semantic object logical attribute information corresponding to the target data, the semantic object logical attribute value corresponding to the target data and the acquired semantic object logical attribute information corresponding to the target data are stored in the logical attribute cache, and based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data, semantic calculation is performed on the target data through the called semantic calculation unit to obtain a corresponding semantic calculation result.

5. The method according to claim 4, wherein the step of calling an external database according to the external data service configured in the object data model to obtain the semantic object logical attribute information corresponding to the target data comprises: Calling an external database according to the external data service configured in the object data model to obtain target semantic object data that matches the semantic object logical attribute value corresponding to the target data; The target semantic object data is converted into semantic object logical attribute information corresponding to the target data based on the logical attribute conversion rules configured in the object data model.

6. The method according to claim 4 or 5, wherein the step of calling an external database according to the external data service configured in the object data model to obtain the semantic object logical attribute information corresponding to the target data comprises: Calling an external database according to the external data service configured in the object data model, and querying whether there is a semantic object logical attribute value corresponding to the target data in the cache of the external database; If it exists, acquiring the semantic object logical attribute information corresponding to the target data from the cache of the external database based on the semantic object logical attribute value corresponding to the target data; If not, the semantic object logical attribute information corresponding to the target data is acquired from the external database based on the semantic object logical attribute value corresponding to the target data.

7. The method according to claim 6, wherein based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data, the semantic calculation unit is called to perform semantic calculation on the target data to obtain the corresponding semantic calculation result, including: Based on the semantic computing logic model in the semantic configuration information corresponding to the target data, obtaining the reference value from a preset reference value set; Based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data, acquiring operator information for performing semantic calculation; By calling the semantic calculation unit, taking the semantic object logical attribute information corresponding to the target data and the obtained reference value as input data, using the obtained operator to perform semantic calculation, and determining the semantic calculation result for the target data.

8. The method according to claim 7, wherein the semantic computing unit comprises a computing semantic computing unit and a merging semantic computing unit. If the semantic computing unit is a computing semantic computing unit, the semantic computing unit that is called uses the semantic object logical attribute information corresponding to the target data and the obtained reference value as input data, uses the obtained operator to perform semantic computing, and determines the semantic computing result for the target data, including: By calling the computing class semantic calculation unit, taking the semantic object logical attribute information corresponding to the target data and the obtained reference value as input data, using the obtained operator to perform semantic calculation, obtaining the semantic calculation result corresponding to the computing class semantic calculation unit, and returning the semantic calculation result corresponding to the computing class semantic calculation unit to the semantic calculation unit at the previous level of the computing class semantic calculation unit to determine the semantic calculation result for the target data; If the semantic calculation unit is a merge-type semantic calculation unit, the semantic calculation unit that is called uses the semantic object logical attribute information corresponding to the target data and the obtained reference value as input data, uses the obtained operator to perform semantic calculation, and determines the semantic calculation result for the target data, including: Obtain output data of a next-level semantic computing unit of the called merging semantic computing unit through the called merging semantic computing unit; The acquired output data is merged to obtain a merged result of the merged semantic computing unit, and the merged result of the merged semantic computing unit is returned to the upper-level semantic computing unit of the merged semantic computing unit to determine the semantic computing result for the target data.

9. According to the method according to claim 8, the object data model also includes one or more of object type, logical attribute identifier and attribute type, the object type includes application, interface and link, the attribute type includes value type and object type, the value type includes text and feature list, and the object type includes application and interface.

10. The method according to claim 1, wherein constructing and outputting the semantic information of the target data based on the semantic configuration information corresponding to the target data and the semantic calculation result comprises: Extracting an output option set and semantic type information from the semantic configuration information corresponding to the target data, wherein the output option set is used to output a specified output value of the semantic output of the output type, and the semantic type information is used to distinguish the type of the semantic calculation result; The semantic information of the target data is constructed and output based on the output option set, the semantic type information and the semantic calculation result.

11. The method according to claim 1, further comprising: Based on the semantic information of the target data, performing data verification processing on the target data or a semantic object corresponding to the target data to obtain a corresponding verification result; or, Based on the semantic information of the target data, a labeling process is performed on the semantic object corresponding to the target data to obtain the labeling information of the semantic object corresponding to the target data.

12. According to the method of claim 1, the target data is data related to data operation under privacy protection business.

13. A data processing device, comprising a semantic computing interface, a semantic configuration module, a semantic logic context module and a semantic computing engine, wherein: The semantic computing interface is configured to receive a semantic acquisition request for target data, wherein the semantic acquisition request includes semantic encoding information and semantic input parameter information; The semantic configuration module is configured to manage configuration information describing the logical semantic rules of the target data, and is configured to obtain semantic configuration information corresponding to the target data based on the semantic encoding information; The semantic logic context module is configured to save and obtain the semantic object logic attribute value corresponding to the target data during the semantic calculation process, and is configured to initialize the semantic object logic attribute value corresponding to the target data based on the semantic input parameter information; The semantic configuration module is configured to call the semantic computing unit in the semantic computing engine based on the semantic configuration information corresponding to the target data; The semantic computing engine is configured to perform semantic computing on the target data based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data by calling a semantic computing unit to obtain corresponding semantic computing results, and to construct and output the semantic information of the target data based on the semantic configuration information corresponding to the target data and the semantic computing results.

14. The apparatus according to claim 13, further comprising an object data model configured to maintain and manage logical attribute information of semantic objects; The semantic logic context module includes a logic attribute submodule and an external data submodule, wherein: The logical attribute submodule queries whether the logical attribute value of the semantic object corresponding to the target data exists in the logical attribute cache based on the initialized logical attribute value of the semantic object corresponding to the target data; if so, determines the logical attribute information of the semantic object corresponding to the target data from the logical attribute cache based on the logical attribute value of the semantic object corresponding to the target data and according to the object data model; The external data submodule, if it does not exist, calls an external database according to the external data service configured in the object data model to obtain the semantic object logical attribute information corresponding to the target data, and stores the semantic object logical attribute value corresponding to the target data and the obtained semantic object logical attribute information corresponding to the target data in the logical attribute cache; The semantic computing engine is configured to perform semantic computing on the target data based on the semantic configuration information corresponding to the target data and the semantic object logical attribute information corresponding to the target data by calling the semantic computing unit to obtain the corresponding semantic computing result.

15. A data processing device, comprising: processor; as well as a memory arranged to store computer executable instructions which, when executed, cause the processor to: Receiving a semantic acquisition request for target data, wherein the semantic acquisition request includes semantic encoding information and semantic input parameter information; Acquire semantic configuration information corresponding to the target data based on the semantic encoding information, and initialize logical attribute values ​​of the semantic object corresponding to the target data based on the semantic input parameter information; Based on the semantic configuration information corresponding to the target data, a semantic calculation unit is called, and based on the semantic configuration information corresponding to the target data and the initialized logical attribute value of the semantic object corresponding to the target data, the called semantic calculation unit performs semantic calculation on the target data to obtain a corresponding semantic calculation result; The semantic information of the target data is constructed and output based on the semantic configuration information corresponding to the target data and the semantic calculation result.

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