Data retrieval method and device, electronic equipment, readable storage medium and chip

Abstract

The invention provides a data retrieval method and device, electronic equipment, a readable storage medium and a chip, and the data retrieval method comprises the steps: obtaining a user retrieval request and an index model; extracting common characteristics of at least one instance data and at least one screening script in the index model; determining a key field corresponding to a user retrieval request; determining a basic attribute corresponding to the key field, wherein the common feature comprises the basic attribute; and determining at least one retrieval result corresponding to the basic attribute according to the screening script. According to the scheme provided by the invention, the instance data corresponding to the basic attributes are loaded on the visual interface in real time by matching all the attribute values, so that the flexibility and expansibility of data retrieval in different models are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data retrieval management, and more particularly, to a data retrieval method, apparatus, electronic device, readable storage medium, and chip. Background Art

[0002] Traditional data retrieval customizes retrieval conditions and retrieval results according to the data that the user wants to display. The data types supported for retrieval are very limited, and the degree of customization is high. Once the model is adjusted or the attributes change, the entire retrieval function will become unusable, and the code needs to be re-adjusted to adapt to the new model and attributes. It is impossible to unify the index data of different models, which will seriously affect the flexibility, expandability, and usability of the program. Summary of the Invention

[0003] In view of this, the present invention aims to solve the problem that the index data of different models in data retrieval cannot be unified.

[0004] Specifically, the present invention is implemented by the following technical solutions:

[0005] In a first aspect of the present invention, a data retrieval method is provided.

[0006] In a second aspect of the present invention, a data retrieval apparatus is provided.

[0007] In a third aspect of the present invention, an electronic device is provided.

[0008] In a fourth aspect of the present invention, a readable storage medium is provided.

[0009] In a fifth aspect of the present invention, a chip is provided.

[0010] The data retrieval method provided by the present invention includes: obtaining a user retrieval request and an index model; extracting common features of at least one instance data and at least one screening script in the index model; determining a keyword field corresponding to the user retrieval request; determining a basic attribute corresponding to the keyword field, where the common features include the basic attribute; and determining at least one retrieval result corresponding to the basic attribute according to the screening script.

[0011] In some technical solutions, optionally, extracting common features of at least one instance data and at least one screening script in the index model includes: determining at least one instance data in the index model; determining type parameters, coding parameters, and inherent attribute types of the instance data according to the index model; and determining common features of at least one instance data according to the type parameters, coding parameters, and inherent attribute types.

[0012] In some technical solutions, optionally, extracting the common features of at least one instance data and at least one screening script in the index model further includes: determining screening parameters according to the index model; determining an instance data screening script and an attribute screening script according to the screening parameters; the instance data screening script is used to determine the index data corresponding to the instance data; the attribute screening script is used to determine the attribute fields corresponding to the basic attributes.

[0013] In some technical solutions, optionally, determining the basic attributes corresponding to the key fields includes: obtaining a historical model database; extracting the basic attributes of at least one model in the historical model database; determining the index data corresponding to at least one model according to the instance data screening script; determining the basic attributes corresponding to the key fields according to the attribute fields.

[0014] In some technical solutions, optionally, determining at least one retrieval result corresponding to the basic attributes according to the screening script includes: obtaining the index data in at least one model; determining the inherent attribute type corresponding to the basic attributes; determining at least one index data corresponding to the user retrieval request according to the screening script; determining the retrieval result according to the index data and the inherent attribute type.

[0015] In some technical solutions, optionally, the inherent attribute type includes basic attributes, at least one associated attribute corresponding to the basic attributes, and at least one reference attribute corresponding to the basic attributes.

[0016] The second aspect of the present invention provides a data retrieval device, which includes: an acquisition module for acquiring a user retrieval request and an index model; an extraction module for extracting the common features of at least one instance data and at least one screening script in the index model; a determination module for determining the key fields corresponding to the user retrieval request; and determining the basic attributes corresponding to the key fields, where the common features include basic attributes; a retrieval module for determining at least one retrieval result corresponding to the basic attributes according to the screening script.

[0017] An embodiment of the third aspect of the present invention provides an electronic device, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor. When the program or instruction is executed by the processor, the steps in the first aspect are implemented.

[0018] An embodiment of the fourth aspect of the present invention provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by the processor, the steps in the first aspect are implemented.

[0019] An embodiment of the fifth aspect of the present invention provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the steps in the first aspect.

[0020] The technical solution provided by the present invention has at least the following beneficial effects:

[0021] The present invention proposes a data retrieval method, which supports the retrieval of basic attributes of all models. By matching all attribute values, the instance data corresponding to the basic attributes is loaded in real time on the visualization interface, improving the flexibility and expandability of data retrieval in different models. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present invention and used together with the specification to explain the principles of the present invention.

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0024] Figure 1 It is a schematic flowchart of the data retrieval method provided by the embodiment of the present invention;

[0025] Figure 2 It is a partial schematic flowchart of the data retrieval method provided by the embodiment of the present invention;

[0026] Figure 3 It is a partial schematic flowchart of the data retrieval method provided by the embodiment of the present invention;

[0027] Figure 4 It is a partial schematic flowchart of the data retrieval method provided by the embodiment of the present invention;

[0028] Figure 5 It is a partial schematic flowchart of the data retrieval method provided by the embodiment of the present invention;

[0029] Figure 6 It is a schematic block diagram of the structure of the data retrieval device provided by the embodiment of the present invention;

[0030] Figure 7 It is a schematic block diagram of the structure of the electronic device provided by the embodiment of the present invention;

[0031] Figure 8 It is a schematic flowchart of the data retrieval method provided by the embodiment of the present invention;

[0032] Figure 9 It is a schematic block diagram of the data retrieval result in the visualization interface provided by the embodiment of the present invention;

[0033] Figure 10Schematic block diagram of data retrieval results in the visualization interface provided by the embodiments of the present invention.

[0034] Among them, Figure 6 and Figure 7 The corresponding relationship between the part names and reference numerals is as follows:

[0035] 900: data retrieval device; 902: acquisition module; 904: extraction module; 906: determination module; 908: retrieval module; 1000: electronic device; 1109: memory; 1110: processor. Detailed implementation manners

[0036] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0037] See Figure 1 , the first aspect of the present invention provides a data retrieval method, including the following steps:

[0038] Step S100: Obtain a user retrieval request and an index model;

[0039] Step S102: Extract the common features of at least one instance data and at least one screening script in the index model;

[0040] Step S104: Determine the keyword field corresponding to the user retrieval request;

[0041] Step S106: Determine the basic attributes corresponding to the keyword field, and the common features include the basic attributes;

[0042] Step S108: Determine at least one retrieval result corresponding to the basic attributes according to the screening script.

[0043] According to the data retrieval method provided by the present invention, instead of retrieving instance data directly, it abstracts the instance data of at least one model into the form of an attribute set by establishing an index model, and retrieves the instance data corresponding to the basic attributes by retrieving the basic attributes. Specifically, the present invention is based on the independently developed Product Data Management (PDM) platform, namely the Haiyun PDM platform. PDM is software-based and is a technology for managing all product-related information (including electronic documents, digital files, database records, etc.) and all product-related processes (including workflow and change process). It can manage any data that can ultimately be converted into computer-readable and storable data. For example: product structure and configuration, part definition and design data, CAD drawing files, engineering analysis and verification data, manufacturing plans and specifications, NC programming files, image files (photos, styling drawings, scanned images, etc.), product manuals, electronic reports, enterprise personnel management tables, project plans, multimedia audio-visual products, and other electronic data. An index model is established from the Haiyun PDM platform, that is, by using the inherent attribute types of the above-mentioned models, including different types of data, the common characteristics corresponding to different models are extracted. Starting from this, a unified index model is established. And obtain the retrieval request sent by the user for the retrieval model. The retrieval request is the requirement of the user to retrieve data of at least one model in the system. The user can determine his retrieval request by inputting any field. Extract the common characteristics of the instance data of at least one model in the historical model database in the index model. The common characteristics include type (i.e., type parameter), encoding (i.e., encoding parameter), and attribute set (i.e., inherent attribute type). The purpose is to classify different data in different models according to attributes or types and unify the data formats in different models. The index model determines the keyword fields corresponding to the user's retrieval request, determines the input fields, deletes the irrelevant fields or strings in the input, determines the fields that already exist in the historical model database, and determines them as keyword fields. By determining the basic attributes that match the keyword fields, for example, the user field corresponding to the enterprise personnel management table or the part field corresponding to the part definition and design data, they are all the fields corresponding to the basic attributes in the model. Search in the historical model database in the way of matching the fields included in the keyword fields and the basic attributes. The index data that matches successfully is used as the retrieval result, and at least one retrieval result is displayed on the visualization interface. When the user clicks on any retrieval result on the visualization interface, the specific instance data is located through the type (i.e., encoding) of the index data, and according to the model relationship of the model knowledge graph in the system, the attribute data related to the retrieved data is displayed.

[0044] Among them, the visualization interface can be any object browser. The basic attributes serve as the main retrieval results of the retrieval results. On the secondary page of the browser, relevant attribute data can be further clicked and redirected to other associated model data to view the complete attribute data corresponding to the keyword fields of the retrieval request.

[0045] It can be understood that through the index model established by the Haiyun PDM platform, a new mode for retrieving data with a unified data format for attributes is created, the common features of at least one model in the historical model database are extracted, the basic attributes of at least one model are retrieved, relevant attribute data is determined, the adaptability and scalability of data retrieval to different models are improved, and the retrieval efficiency of users for retrieving different models is improved.

[0046] In some embodiments, optionally, as Figure 2 shown, extracting the common features of at least one instance data and at least one screening script in the index model includes:

[0047] Step S1022: Determine at least one instance data in the index model;

[0048] Step S1024: Determine the type parameter, coding parameter, and inherent attribute type of the instance data according to the index model;

[0049] Step S1026: Determine the common features of at least one instance data according to the type parameter, coding parameter, and inherent attribute type.

[0050] In this embodiment, at least one instance data in the index model is determined, that is, the instance data corresponding to at least one model in the historical model database. The instance data includes the data in the corresponding model, and the type, coding, and inherent attribute type corresponding to the instance data are determined according to the index model, where the inherent attribute type includes basic attributes, reference attributes, and associated attributes. Specifically, the type parameter of the data is the data type in the model corresponding to the data stored in the model, which can be a text type or other type forms such as pictures. The coding parameter is the coding (Identity document, ID) corresponding to the data, that is, the serial number or account parameter stored in the model, and the basic attributes, reference attributes, and associated attributes of the data are uniformly extracted as the inherent attribute type (i.e., the attribute set) of the data. By extracting the type parameter, coding parameter, and inherent attribute type of the instance data, the common features of at least one instance data in the historical model database are determined through the index model, the data format is unified, the data processing volume is reduced, and the retrieval efficiency is improved.

[0051] In some embodiments, optionally, as Figure 3 shown, extracting the common features of at least one instance data and at least one screening script in the index model further includes:

[0052] Step S1028: Determine the screening parameters according to the index model;

[0053] Step S1030: Determine the instance data screening script and the attribute screening script according to the screening parameters;

[0054] The instance data screening script is used to determine the index data corresponding to the instance data; the attribute screening script is used to determine the attribute fields corresponding to the basic attributes.

[0055] In this embodiment, the screening parameters are determined through the index model. The screening parameter is the string matching degree. When the matching degree between the field corresponding to the basic attribute of the instance data in the model (i.e., the attribute field) and the keyword field corresponding to the user's retrieval request is greater than the string matching degree (i.e., the screening parameter), it is determined that the keyword field corresponding to the user's retrieval request matches the basic attribute of the instance data; when the matching degree between the field corresponding to the basic attribute of the instance data (i.e., the attribute field) and the preset string is greater than the string matching degree (i.e., the screening parameter), an index condition is established for the instance data, that is, the instance data exists as index data in the index model. When the matching degree between the field corresponding to the basic attribute of the instance data (i.e., the attribute field) and the preset string is less than the string matching degree (i.e., the screening parameter), the basic attribute of the instance data is stored as reference attribute or associated attribute data in the index model. Among them, the string matching degree (i.e., the screening parameter) and the preset string are both set by the enterprise operator.

[0056] It can be understood that by setting the instance screening script and the attribute screening script, the flexibility of the retrieval result of the index model configuration is improved, and the accuracy of the user searching for data during the data retrieval process is improved.

[0057] In some embodiments, optionally, as Figure 4 shown, determining the basic attribute corresponding to the keyword field includes:

[0058] Step S1062: Obtain the historical model database;

[0059] Step S1064: Extract the basic attributes of at least one model in the historical model database;

[0060] Step S1066: Determine the index data corresponding to at least one model according to the instance data screening script;

[0061] Step S1068: Determine the basic attribute corresponding to the keyword field according to the attribute field.

[0062] In this embodiment, a historical model database is obtained. The historical model database is a database composed of at least one product data model such as product structure and configuration, part definition and design data, CAD drawing files, engineering analysis and verification data, manufacturing plans and specifications, NC programming files, image files (photos, styling drawings, scanned images, etc.), product manuals, electronic reports, enterprise personnel management tables, project plans, multimedia audio-visual products, and other electronic data. The basic attributes of all product data models in the database are extracted according to the index model, and the index data corresponding to the instance data screening script is determined according to the index model. That is, when the field corresponding to the basic attribute of the instance data (i.e., the attribute field) has a greater degree of string matching with the preset string than the string matching degree (i.e., the screening parameter), an index condition is established for the instance data, and the basic attribute corresponding to the keyword field is determined according to the matching degree of the attribute field, that is, the basic attribute that meets the keyword field matching requirements.

[0063] In some embodiments, optionally, as Figure 5 shown, at least one retrieval result corresponding to the basic attribute is determined according to the screening script, including:

[0064] Step S1082: Obtain the index data in at least one model;

[0065] Step S1084: Determine the inherent attribute type corresponding to the basic attribute;

[0066] Step S1086: Determine at least one index data corresponding to the user's retrieval request according to the screening script;

[0067] Step S1088: Determine the retrieval result according to the index data and the inherent attribute type.

[0068] In this embodiment, the index data in the historical model database is obtained, and the inherent attribute type of the basic attribute corresponding to the index data is determined, that is, the associated attributes and reference attributes related to the basic attribute. According to the screening script rules, the attribute fields corresponding to the index data in the model database are matched to determine the corresponding instance data and basic attributes. The instance data and basic attributes are displayed as index data on the visualization interface, and the associated attributes and reference attributes corresponding to the basic attributes are determined according to the knowledge graph corresponding to the model. The user can choose to browse in the secondary page of the visualization interface. The index model determines the index data and the inherent attribute type as the retrieval result for a brief preview on the visualization interface. That is, when browsing the retrieval result, not only the basic attribute can be displayed, but also the reference attributes and associated attributes can be loaded in real time through the knowledge graph where the model is located, and the user can click to jump to the relevant instance data to browse the retrieval result.

[0069] In some embodiments, optionally, the inherent attribute types include basic attributes, at least one associated attribute corresponding to the basic attributes, and at least one reference attribute corresponding to the basic attributes.

[0070] In this embodiment, based on the retrieved search results, the corresponding index data and basic attributes are determined. When browsing the search results on the visualization interface (i.e., the object browser page), not only the basic attributes corresponding to the keyword fields input by the user can be displayed, but also the reference attributes and associated attributes can be loaded in real time on the visualization interface through the knowledge graph where the model is located. The user can view at least one associated attribute data and at least one reference attribute data corresponding to the basic attributes on the visualization interface, where the associated attributes and reference attributes are determined by the knowledge graph corresponding to the model. The user can jump to the relevant instance data for browsing on the visualization interface by clicking on any associated attribute or reference attribute in the page. It can be understood that the data retrieval method provided by the present invention can be used regardless of how the model corresponding to the user's search request changes.

[0071] In a specific embodiment, the flowchart of the data retrieval method based on the knowledge graph is as Figure 8 shown, including:

[0072] Step S302: Configure the index type; Step S304: Configure the index attributes; Step S306: Configure the renderer; Step S308: Configure the content displayed in the object browser; Step S402: Generate the index object; Step S404: Retrieve the index object; Step S406: Render the retrieval effect; Step S408: Jump to the browsing interface; Step S410: Browse the object browsing interface.

[0073] In this embodiment, instance data (Entity) in at least one model is configured within the system. The instance data refers to specific instances. An entity can be understood as an entity or a type, which is an abstraction of a class of things. An entity is associated with properties. A property is a basic attribute of an entity. The definition of each entity determines a table, which contains the definition of the associated basic attributes. For example, specific instances of at least one type in an enterprise personnel management table. The instance data can be displayed in a visual browser interface within the system. Specifically, by configuring the index type and index attributes (i.e., basic attributes) corresponding to the instance data, an index object (i.e., index data) is generated. The system can retrieve the index object by matching the user input field and the configured index attributes, and determine the index data corresponding to the user input field. The display configuration of the index data in the visual browser interface includes: configuring a renderer and configuring the display content of the object browser. By configuring the renderer, a retrieval effect is rendered for the instance data and a jump browsing interface corresponding to the instance data is set. That is, the retrieval display effect of the index data on the browser interface is rendered by the renderer, and relevant display settings for jumping from the data field to the browsing interface are set; and the display content of the object browser is configured for the instance data to determine the browsing interface of the browsing object, enabling the user to browse the browsing interface corresponding to the instance data in different browsers.

[0074] It can be understood that by configuring a renderer and configuring the display content of the object browser for the instance data (Entity), the instance data in each model has different display effects on different browser interfaces, improving the personalization of data retrieval and the adaptability between the model and the browser.

[0075] In a specific embodiment, the data retrieval method includes:

[0076] Step 1: Establish an index model in the independently developed PDM platform (hereinafter collectively referred to as Haiyun PDM), and abstract the common characteristics (type, ID, attribute set) of all instance data;

[0077] Step 2: Extract the basic attributes of each model, establish index data for the instance data of each model, and save all basic attributes into the attribute set as the target for keyword matching;

[0078] Step 3: Obtain the instance data screening script customized for the model. Only the instance data that meets the script conditions will establish an index, achieving the purpose of flexibly configuring the retrieval results;

[0079] Step 4: Obtain the attribute screening script customized for the model to achieve the purpose of flexibly configuring the display of instance attributes;

[0080] Step 5: When the user enters a keyword for search, all successfully matched index data are found and the attribute set is displayed in the search results;

[0081] Step 6. Click on any search result, locate the instance object by the type and ID in the index data, and display the basic attributes, reference attributes, and associated attributes of the search data according to the model relationship in the knowledge graph;

[0082] Step 7. In the object browser, you can continue to click reference properties or associated properties to jump to other associated model data and browse its complete properties.

[0083] In this embodiment, the data retrieval method uses the inherent attribute types of the model, namely basic attributes, reference attributes, and associated attributes, to extract the common features of all models, and uses this as a starting point to establish a unified index mode; it does not search for instance data, because the instance data of different models are ever-changing, and the number of database tables is huge, and it is impossible to achieve a retrieval method that satisfies the retrieval of all database tables. Therefore, an index model is established, and the instance data of all models can be abstracted into instance types, instance IDs, and instance attribute sets to unify the data format. There is no fixed search condition. The keywords entered by the user are used to match all attribute values. Any attribute value containing keywords will be retrieved. When browsing the search results, not only the basic attributes can be displayed, but also the reference attributes and associated attributes can be loaded in real time through the knowledge graph where the model is located, and you can click to jump to the relevant instance data for browsing. No matter how the model changes, this retrieval method can be used and is highly universal.

[0084] It can be understood that the data retrieval method supports the basic attribute retrieval of various models, the linked browsing of relevant data of any retrieval result, and the extraction of commonalities of all model data, and the retrieval for a unified data format, which improves the flexibility, scalability and availability of data retrieval.

[0085] In a specific embodiment, optionally, the data retrieval method includes:

[0086] Step 1: The developer finds the user model (HCUser) in the model structure tree of Haiyun PDM, and right-clicks the menu to enter "Index Configuration";

[0087] Step 2: Add the basic attributes that HCUser needs to index to the list. As shown in Table 1, the basic names corresponding to the basic attributes include: Name, Number, Description, Phone, Mobile, Birthday, Email, Full Name, and Gender. The name is an English string corresponding to the display name, specifically including: Name, Sn, Description, Phone, Mobile, Brith, Emall, Fullname, and Sex. The name and the display name are in one-to-one correspondence, and the status of each display name is marked. The status includes: Display and Do not display. By setting the status of the display name, the basic attributes that you want to display can be set in the visualization interface;

[0088] Name Display Name Status Name Name Display Sn Number Display Description Description Display Phone Phone Display Mobile Mobile Phone Display Brith Birthday Display Emall Email Display Fullname Full Name Display Sex Gender Display

[0089] Table 1

[0090] Step 3: The developer finds the user model (HCUser) in the model structure tree of Haiyun PDM and enters "Object Browser Configuration" through the right-click menu;

[0091] Step 4: Add the basic attributes that HCUser needs to display to the list, as shown in Table 1;

[0092] Step 5: Execute the create index script to automatically generate all instance data and related attribute sets of HCUser into the index table;

[0093] Step 6: Enter the search page of Haiyun PDM, input any user attribute value (and the keyword field corresponding to the retrieval request), and retrieve all matching results. As Figure 9 shown, when the user inputs the attribute value as "user", the system will retrieve the basic attributes corresponding to the keyword field of "user" and match the index data of the corresponding user basic attributes within the system. The display results are as follows: User Name XXX1, Number u2005068, Gender Male; User Name XXX2, Number u2005241, Gender Male; User Name XXX3, Number u2004033, Gender Male; User Name XXX4, Number u1990039, Gender Male and 76 related results. Among them, the 76 related results are all instance data with the basic attribute of "user".

[0094] Step 7: Click on any retrieval result to enter the user browsing page, display the user's basic attributes, and load reference attributes and associated attributes according to the knowledge graph where the user is located, such as attached Figure 10As shown, when the index data of user XXX1 is clicked, the basic attributes, associated attributes, and reference attributes corresponding to the index data will be displayed on the secondary page. Specifically, in the visualization interface, a navigation bar is displayed on the left side of the page, and attributes, relationships, and references are displayed under the object corresponding column. Among them, the attributes include: name, number, description, phone, mobile phone, birthday, email, full name, gender, and other basic attributes, which are set in step two. The relationships include: Department, Task, User, affiliated role, and affiliated group. The references include deployment objects. The relationship column and the reference column are determined by the relevant attribute set. The specific items corresponding to the basic attributes are displayed on the right side of the page, such as the number, description, phone, mobile phone, birthday, email, full name, and gender details of name XXX1, as well as the object corresponding to the user name XXX1, the object is the Planning and Operation Section, the name is the Object Operation Section, the serial number corresponding to the Object Operation Section is 1, the number is Depart-0-01-07-02, abbreviated as Planning, and its special annotation (Specially) is artificial (False). And the specific contents of the relationships and references in the relevant attribute set are displayed below, such as the specific contents of Department, Task, User, and affiliated role under the relationship column.

[0095] Step Eight: Click on the attribute under the relationship in the display page to jump to view the department, role, etc. of the user.

[0096] As Figure 6 As shown, in the second aspect of the present invention, a data retrieval device 900 is provided. The data retrieval device 900 includes: an acquisition module 902 for acquiring a user retrieval request and an index model; an extraction module 904 for extracting the common features of at least one instance data and at least one screening script in the index model; a determination module 906 for determining the keyword fields corresponding to the user retrieval request; and determining the basic attributes corresponding to the keyword fields, where the common features include basic attributes; a retrieval module 908 for determining at least one retrieval result corresponding to the basic attributes according to the screening script.

[0097] In this embodiment, the data retrieval device 900 establishes an index model to abstract the instance data of at least one model into the form of an attribute set, and retrieves the instance data corresponding to the basic attributes by using the keyword fields corresponding to the retrieval request input by the user. Specifically, the acquisition module 902 acquires the Product Data Management (PDM) platform, that is, the Haiyun PDM platform, and establishes an index model from the Haiyun PDM platform. That is, by using the inherent attribute types of the above-mentioned various models, including different types of data, the common features corresponding to different models are extracted. Starting from this, a unified index model is established. After obtaining the index model, the retrieval request input by the user into the system is acquired. The extraction module 904 extracts the type, code, and inherent attribute type corresponding to the instance data through the index model. The inherent attribute type includes basic attributes, reference attributes, and associated attributes, and determines the type parameter, code parameter, and inherent attribute type as the common features corresponding to the instance data; and determines the instance data screening script and attribute screening script according to the index model. The determination module 906 matches the keyword fields corresponding to the retrieval request input by the user into the system by matching the fields that already exist in the historical model database, and determines the basic attributes that match the keyword fields corresponding to the retrieval request through the screening script. The retrieval module 908 acquires the index data in the historical model database, and determines the inherent attribute type of the basic attributes corresponding to the index data, that is, the associated attributes and reference attributes related to the basic attributes. According to the screening script rules, the attribute fields corresponding to the index data in the model database are matched to determine the corresponding instance data and basic attributes, and the instance data and basic attributes are displayed as index data on the visualization interface, and the associated attributes and reference attributes corresponding to the basic attributes are determined according to the knowledge graph corresponding to the model, completing the display of the retrieval result of the retrieval request input by the user. By establishing an index model from the PDM platform through the data retrieval device 900 and acquiring the user's retrieval instruction, extracting the common features of at least one model in the historical model database, retrieving the basic attributes of at least one model, determining the relevant attribute data, and displaying the retrieval result in the visualization interface, the scalability of data retrieval for different models and the usability of users are improved.

[0098] As Figure 7 shown, a third aspect of the present invention provides an electronic device 1000, including a processor 1110, a memory 1109, a program or instruction stored on the memory 1109 and executable on the processor 1110. When the program or instruction is executed by the processor 1110, it implements each process of the embodiment of the above data retrieval method and can achieve the same technical effect. To avoid repetition, it will not be described here again.

[0099] Among them, the processor 1110 is configured to obtain a user retrieval request and an index model; extract common features of at least one instance data and at least one screening script in the index model; determine keyword fields corresponding to the user retrieval request; determine basic attributes corresponding to the keyword fields, where the common features include basic attributes; and determine at least one retrieval result corresponding to the basic attributes according to the screening script.

[0100] Optionally, the processor 1110 is further configured to determine at least one instance data in the index model; determine type parameters, encoding parameters, and inherent attribute types of the instance data according to the index model; and determine common features of at least one instance data according to the type parameters, encoding parameters, and inherent attribute types.

[0101] Optionally, the processor 1110 is further configured to determine screening parameters according to the index model; and determine an instance data screening script and an attribute screening script according to the screening parameters.

[0102] Optionally, the processor 1110 is further configured to extract basic attributes of at least one model in the historical model database; determine index data corresponding to at least one model according to the instance data screening script; and determine basic attributes corresponding to the keyword fields according to the attribute fields.

[0103] Optionally, the processor 1110 is further configured to obtain index data in at least one model; determine the inherent attribute type corresponding to the basic attributes; determine at least one index data corresponding to the user retrieval request according to the inherent attribute type; and determine the retrieval result according to the index data and the inherent attribute type.

[0104] A fourth aspect of the present invention provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, it implements each process of the embodiment of the above data retrieval method and can achieve the same technical effect. To avoid repetition, it will not be elaborated here. In addition, the readable storage medium improves the data storage capacity and data processing speed corresponding to the data retrieval method in the present application.

[0105] The method can be implemented in various different ways according to specific features and / or example applications. For example, these methods can be implemented by a combination of hardware, firmware, and / or software. For example, in a hardware implementation, the processor can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, electronic devices, other device units for performing the above functions, and / or combinations thereof.

[0106] A computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium can be an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing devices, but is not limited thereto. A non-exhaustive list of more specific examples of computer-readable storage media includes: portable computer floppy disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital versatile discs (DVDs), memory cards, floppy disks, encoding mechanical devices (such as punched cards or grooves with raised structures recording instructions), and any suitable combination of the foregoing devices. The computer-readable storage medium used herein should not be construed as a signal per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media, or electrical signals transmitted through wires, etc.

[0107] Among them, the processor is the processor in the electronic device in the foregoing embodiment. The readable storage medium includes computer-readable storage media, such as computer read-only memory (Read-Only Memory, ROM), random access memory (RandomAccess Memory, RAM), magnetic disks, or optical discs, etc.

[0108] The fifth aspect of the present invention provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement each process of the embodiment of the above data retrieval method and can achieve the same technical effects. To avoid repetition, it will not be elaborated here. In addition, the chip improves the data processing speed corresponding to the data retrieval method in this application.

[0109] Although this specification contains many specific implementation details, these should not be construed as limiting the scope of any invention or the scope of what is claimed, but are mainly used to describe the features of specific embodiments of a particular invention. Certain features described in multiple embodiments in this specification can also be combined and implemented in a single embodiment. On the other hand, various features described in a single embodiment can also be separately implemented in multiple embodiments or implemented in any suitable sub-combination. In addition, although features may function in certain combinations as described above and are even initially claimed as such, one or more features from the claimed combination can in some cases be removed from the combination, and the claimed combination can be directed to a sub-combination or a variant of the sub-combination.

[0110] Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that these operations be performed in the particular order shown or performed sequentially, or requiring that all illustrated operations be performed to achieve the desired results. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system modules and components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product, or packaged into multiple software products.

[0111] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some implementations, multitasking and parallel processing may be advantageous.

[0112] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article 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, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0113] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A data retrieval method, characterized in that: include: Get user retrieval request and index model; Extracting common features of at least one instance data in the index model and at least one screening script; Determine the key fields corresponding to the user search request; Determining basic attributes corresponding to the key fields, the common features including the basic attributes; At least one search result corresponding to the basic attribute is determined according to the screening script.

2. The data retrieval method according to claim 1, characterized in that: The extracting common features of at least one instance data in the index model and at least one screening script includes: Determining at least one instance data in the index model; Determine type parameters, encoding parameters and intrinsic attribute types of the instance data according to the index model; At least one common feature of the instance data is determined according to the type parameter, the encoding parameter and the inherent attribute type.

3. The data retrieval method according to claim 1, characterized in that: The extracting of the common features of at least one instance data in the index model and at least one screening script also includes: Determining screening parameters according to the index model; Determine an instance data screening script and an attribute screening script according to the screening parameters; The instance data screening script is used to determine index data corresponding to the instance data; The attribute screening script is used to determine the attribute field corresponding to the basic attribute.

4. The data retrieval method according to claim 3, characterized in that: The determining of the basic attributes corresponding to the key field includes: Obtain historical model database; Extracting basic attributes of at least one model in the historical model database; Determining the index data corresponding to at least one of the models according to the instance data screening script; The basic attribute corresponding to the key field is determined according to the attribute field.

5. The data retrieval method according to any one of claims 1 to 4, characterized in that: The determining, according to the screening script, at least one search result corresponding to the basic attribute comprises: Obtaining index data in at least one of the models; determining an intrinsic attribute type corresponding to the basic attribute; Determine at least one of the index data corresponding to the user's search request according to the screening script; A search result is determined based on the index data and the inherent attribute type.

6. The data retrieval method according to claim 2, characterized in that: The intrinsic attribute type includes a basic attribute, at least one associated attribute corresponding to the basic attribute, and at least one reference attribute corresponding to the basic attribute.

7. A data retrieval device, characterized in that: include: The acquisition module is used to obtain user search requests and index models; An extraction module, used for extracting common features of at least one instance data in the index model and at least one screening script; A determination module, used to determine a key field corresponding to the user's search request; and determining basic attributes corresponding to the key fields, the common features including the basic attributes; A retrieval module is used to determine at least one retrieval result corresponding to the basic attribute according to the screening script.

8. An electronic device, characterized in that: The method comprises a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method according to any one of claims 1 to 6.

9. A readable storage medium, characterized in that: The readable storage medium stores a program or an instruction, and when the program or the instruction is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A chip, characterized in that: The chip includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or an instruction to implement the steps of the method according to any one of claims 1 to 6.

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