Data processing method and apparatus, device, and storage medium

Abstract

Embodiments of the present disclosure provide a data processing method and apparatus, a device, and a storage medium. The method comprises: receiving a selection with respect to a target portion in a data object, the target portion containing reference content; on the basis of the target portion in the data object and at least part of the reference content, generating a target vectorized representation corresponding to the target portion; and storing the target vectorized representation in a knowledge base, so as to use at least one of the following as a query result of querying performed for the data object: at least a portion in the target portion, and the at least part of the reference content. In this way, an application creation user can store vectorized representations of reference content of data objects in batches in a knowledge base to expand the knowledge inventory of the knowledge base, which advantageously improves the quality of a query result provided to a terminal user.

Description

Data processing method, device, equipment and storage medium

[0001] This application claims priority to the Chinese invention patent application entitled “Method, device, equipment and storage medium for data processing” and application number 202311569253.6, filed on November 22, 2023. The entire contents of that application are incorporated by reference into this application. Technical Field

[0002] Example embodiments of the present disclosure generally relate to the field of computers, and more particularly, to methods, devices, apparatuses, and computer-readable storage media for data processing. Background Art

[0003] With the development of information technology, various terminal devices can provide people with a variety of services in work and life. Applications that provide these services can be deployed on these devices. These applications present content and interact with users through their user interfaces, meeting their needs. In some cases, users may initiate queries within applications. Therefore, providing users with structured data as knowledge to improve the quality of query results is a key concern.

[0004] Summary of the Invention

[0005] In a first aspect of the present disclosure, a method for data processing is provided. The method includes: receiving a selection of a target portion in a data object, the target portion having reference content; generating a target vectorized representation corresponding to the target portion based on the target portion in the data object and at least a portion of the reference content; and storing the target vectorized representation in a knowledge base for use as a query result in a query for the data object using at least one of the following: at least a portion of the target portion and at least a portion of the reference content.

[0006] In a second aspect of the present disclosure, a method for data processing is provided. The method includes: receiving a query for a data object; determining a target vectorized representation matching the query from a knowledge base, the target vectorized representation generated based on a target portion in the data object and at least a portion of a referenced content of the target portion; and determining a result of the query based on the target vectorized representation, the result of the query indicating at least one of the following: at least a portion of the target portion and at least a portion of the referenced content.

[0007] In a third aspect of the present disclosure, a data processing apparatus is provided. The apparatus includes: a selection receiving module configured to receive a selection of a target portion in a data object, the target portion having referenced content; a target vectorized representation generating module configured to generate a target vectorized representation corresponding to the target portion based on the target portion in the data object and at least a portion of the referenced content; and a target vectorized representation storing module configured to store the target vectorized representation in a knowledge base, for use in a query targeting the data object as a query result of at least one of the following: at least a portion of the target portion and at least a portion of the referenced content.

[0008] A fourth aspect of the present disclosure provides a data processing apparatus. The apparatus includes: a query receiving module configured to receive a query for a data object; a target vectorized representation determining module configured to determine a target vectorized representation matching the query from a knowledge base, the target vectorized representation generated based on a target portion in the data object and at least a portion of the referenced content of the target portion; and a query result determining module configured to determine a result of the query based on the target vectorized representation, the result of the query indicating at least one of the following: at least a portion of the target portion and at least a portion of the referenced content.

[0009] In a fifth aspect of the present disclosure, an electronic device is provided. The device includes at least one processing unit; and at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit. When executed by the at least one processing unit, the instructions cause the electronic device to perform the methods of the first and second aspects.

[0010] In a sixth aspect of the present disclosure, a computer-readable storage medium is provided, wherein a computer program is stored on the medium, and when the computer program is executed by a processor, the methods of the first and second aspects are implemented.

[0011] In a seventh aspect of the present disclosure, a computer program product is provided. The computer program product is tangibly stored in a computer storage medium and includes computer-executable instructions. When executed by a device, the computer-executable instructions cause the device to perform the methods of the first and second aspects. It should be understood that the content described in this section is not intended to limit the key features or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0013] FIG1 shows a schematic diagram of an example environment in which embodiments of the present disclosure can be implemented;

[0014] FIG2 shows a schematic diagram of transferring data to a knowledge base according to some embodiments of the present disclosure;

[0015] FIG3 shows an example of a page for selecting fields in a data table according to some embodiments of the present disclosure;

[0016] FIG4 shows an example of a page for selecting a reference content type for a text type field according to some embodiments of the present disclosure;

[0017] FIG5 shows an example of a page for selecting a reference content type for a value type field according to some embodiments of the present disclosure;

[0018] FIG6 shows an example of a page of query results according to some embodiments of the present disclosure;

[0019] FIG7 shows an example of a page showing a learning status of reference contents of various fields in a data table by a knowledge base according to some embodiments of the present disclosure;

[0020] FIG8A shows a flowchart of a data processing process according to some embodiments of the present disclosure;

[0021] FIG8B shows a flowchart of another process of data processing according to some embodiments of the present disclosure;

[0022] FIG9A shows a schematic structural block diagram of a data processing apparatus according to some embodiments of the present disclosure;

[0023] FIG9B shows a schematic structural block diagram of another apparatus for data processing according to some embodiments of the present disclosure; and

[0024] FIG10 shows a block diagram of an electronic device in which one or more embodiments of the present disclosure may be implemented. DETAILED DESCRIPTION

[0025] The following describes embodiments of the present disclosure in more detail with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0026] In the description of the embodiments of the present disclosure, the term "including" and similar terms should be understood as open inclusion, i.e., "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". Other explicit and implicit definitions may be included below.

[0027] Herein, unless explicitly stated otherwise, executing a step “in response to A” does not mean executing the step immediately after “A” but may include one or more intermediate steps.

[0028] It is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition, use, storage or deletion of the data) shall comply with the requirements of relevant laws, regulations and relevant provisions.

[0029] It is understandable that before using the technical solutions disclosed in the various embodiments of the present disclosure, the type, scope of use, usage scenarios, etc. of the information involved in the present disclosure should be informed to relevant users and authorization should be obtained from relevant users in an appropriate manner in accordance with relevant laws and regulations. The relevant users may include any type of right holders, such as individuals, enterprises, and groups.

[0030] For example, in response to receiving an active request from a user, a prompt message is sent to the relevant user to clearly prompt the relevant user that the operation requested to be performed will require obtaining and using the information of the relevant user, so that the relevant user can independently choose whether to provide information to the software or hardware such as the electronic device, application, server or storage medium that executes the operation of the technical solution of the present disclosure based on the prompt message.

[0031] As an optional but non-limiting implementation, in response to receiving an active request from a relevant user, a prompt message may be sent to the relevant user in the form of a pop-up window, in which the prompt message may be presented in text form. Furthermore, the pop-up window may also include a selection control for the user to select "agree" or "disagree" to provide information to the electronic device.

[0032] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0033] As used herein, the term "model" can learn the association between corresponding inputs and outputs from training data, so that after training is completed, corresponding outputs can be generated for given inputs. The generation of the model can be based on machine learning technology. Deep learning is a machine learning algorithm that processes inputs and provides corresponding outputs by using multiple layers of processing units. A neural network model is an example of a model based on deep learning. In this article, "model" may also be referred to as "machine learning model", "learning model", "machine learning network" or "learning network", and these terms are used interchangeably in this article.

[0034] FIG1 illustrates a schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented. Environment 100 includes an application management platform 110, which can support the creation and / or execution of applications. In some embodiments, the portion of application management platform 110 that supports application creation can also be referred to as an application creation portion. In some embodiments, the portion of application management platform 110 that supports application execution can also be referred to as an application execution portion.

[0035] As shown in Figure 1, the application creation part can provide a user 105 with an environment for creating and publishing applications. User 105 can be referred to as an application creation user or creator. In some embodiments, the application creation part can be a low-code platform that provides a collection of tools for application creation. The application creation part can support visual development of various types of applications, allowing developers to skip the manual coding process and speed up the application development cycle and cost. The application creation part can support any appropriate platform for users to develop one or more types of applications, for example, it can include a platform based on Application Platform as a Service (aPaaS). Such a platform can support users to efficiently develop applications and implement operations such as application creation and application function adjustment.

[0036] The application creation part can be deployed locally on the terminal device of user 105, and / or can be supported by a server-side device. For example, the terminal device of user 105 can run a client of the application creation part, which can support the interaction between the user and the application creation part provided by the server. In the case where the application creation part runs locally on the user's terminal device, user 105 can directly use the terminal device to interact with the local application creation part. In the case where the application creation part runs on the server-side device, the server-side device can realize the service provision of the client running in the terminal device based on the communication connection between the terminal device. The application creation part can present a corresponding page 130 to the user 105 based on the operation of the user 105 to output and / or receive information related to application creation to the user 105 and / or from the user 105.

[0037] In some embodiments, the application creation portion can be associated with a corresponding database, which stores the data or information required for the application creation process supported by the application creation portion. For example, the database can store the code and description information corresponding to each functional module used to make up the application. The application creation portion can also perform operations such as calling, adding, deleting, and updating the functional modules in the database. The database can also store operations that can be performed on different functional blocks. For example, in a scenario where an application is to be created, the application creation portion can call the corresponding functional blocks from the database to build the application.

[0038] In an embodiment of the present disclosure, a user 105 can create a target application 120 as needed in the application creation section and publish the target application 120. The target application 120 can be published to any appropriate application execution section, as long as the application execution section can support the operation of the target application 120. After publication, the target application 120 can be used to be operated by one or more users 145. The user 145 can be referred to as the end user of the target application 120. In some embodiments, the target application 120 may include or be implemented as a digital assistant 122.

[0039] The digital assistant 122 can be configured to have intelligent dialogue. In the example shown in Figure 1, the digital assistant 122 can be integrated into the target application 120 and assist in executing task processing within the target application 120 as a part of the target application 120. In other examples, the digital assistant 122 can be configured as an independently running application, such as a web application or other types of applications. In such an example, the digital assistant 122 and the target application 120 can be regarded as the same application. The digital assistant 122 is provided to assist users with various task processing needs in different applications and scenarios. During the interaction with the digital assistant 122, the user inputs an interactive message, and the digital assistant 122 provides a reply message in response to the user input. Generally, the digital assistant 122 can support users to input questions in natural language, and perform tasks and provide replies based on the understanding of natural language input and logical reasoning ability.

[0040] In some embodiments, digital assistant 122 can interact with user 145 as a contact. For example, digital assistant 122 can be implemented in an instant messaging (IM) application. Digital assistant 122 can interact with user 145 in a single chat session with user 145. In some embodiments, digital assistant 122 can interact with multiple users in a group chat session including multiple users.

[0041] For each user 145, the client of the application running portion can present an interaction window 142 of the target application 120 or the digital assistant 122 in the client interface, such as a conversation window with the digital assistant 122. The user 145 can enter a conversation message in the conversation window, and the target application 120 can determine a reply message of the digital assistant 122 based on the created configuration information and present it to the user in the interaction window 142. In some embodiments, depending on the configuration of the target application 120, the interaction message with the target application 120 can include messages in multimodal forms, such as text messages (e.g., natural language text), voice messages, image messages, video messages, etc.

[0042] Similar to the application creation part, the application running part can be deployed locally on the terminal device of each user 145, and / or can be supported by a server-side device. For example, the terminal device of user 145 can run a client with the application running part, which can support the interaction between the user and the application running part provided by the server. In the case where the application running part runs locally on the user's terminal device, the user 145 can directly use the terminal device to interact with the local application running part. In the case where the application running part runs on the server-side device, the server-side device can realize the service provision of the client running in the terminal device based on the communication connection between the terminal device. The application running part can present the corresponding application page to the user 145 based on the operation of the user 145, so as to output and / or receive information related to the use of the application to the user 145 and / or receive information from the user 145 from the user 145.

[0043] In some embodiments, at least some of the functionality of the target application 120 and / or at least some of the functionality of the digital assistant 122 in the target application 120 can be implemented based on a model. During the creation or execution of the target application 120, one or more models 155, such as the capabilities of the models 155, can be invoked. In the target application 120, the digital assistant 122 can utilize the models 155 to understand user input and provide responses to the user based on the output of the models 155.

[0044] During the creation process, the application management platform 110 tests the target application 120 using the model 155 to ensure that the target application 120's operating results meet expectations. During operation, in response to various user operation requests of the target application 120, the application execution component may need to use the model 155 to determine the user's response results.

[0045] Although shown as being independent of the application management platform 110, one or more models 155 can run on the application management platform 110 or other remote servers. In some embodiments, the model 155 can be a machine learning model, a deep learning model, a learning model, a neural network, etc. In some embodiments, the model can be based on a language model (LM). A language model can have question-answering capabilities by learning from a large amount of corpus. The model 155 can also be based on other appropriate models.

[0046] The application management platform 110 can run on appropriate electronic devices. The electronic devices here can be any type of device with computing capabilities, including terminal devices or server devices. The terminal device can be any type of mobile terminal, fixed terminal or portable terminal, including mobile phones, desktop computers, laptop computers, notebook computers, netbook computers, tablet computers, media computers, multimedia tablets, personal communication systems (PCS) devices, personal navigation devices, personal digital assistants (PDAs), audio / video players, digital cameras / camcorders, positioning devices, television receivers, radio broadcast receivers, e-book devices, gaming devices or any combination of the foregoing, including accessories and peripherals of these devices or any combination thereof. The server device can, for example, include a computing system / server, such as a mainframe, an edge computing node, a computing device in a cloud environment, and the like. In some embodiments, the management platform 110 can be implemented based on cloud services.

[0047] It should be understood that the structure and functionality of the environment 100 are described for exemplary purposes only and do not imply any limitation on the scope of the present disclosure. For example, although FIG1 illustrates a single user interacting with the application creation portion and a single user interacting with the application execution portion, in practice multiple users may access the application management platform 110 to each create a digital assistant, and each digital assistant may be used to interact with multiple users.

[0048] When a user initiates a query within an application, the application can provide answer services based on the knowledge base. The knowledge base stores data related to the query. In some cases, it may be necessary to use structured data (e.g., data tables, data objects) as knowledge to provide question-and-answer services. In some cases, it may be necessary to use unstructured data (e.g., documents, web pages, etc.) as knowledge to provide question-and-answer services. Therefore, these structured data and / or unstructured data can be stored in a knowledge base. These data may include links that reference other content (e.g., documents). The content in these links is usually valuable. If the content in these links is stored in the knowledge base, it will be beneficial to improve the instructions for question-and-answer services.

[0049] To this end, a data processing solution is provided according to an embodiment of the present disclosure. According to various embodiments of the present disclosure, a selection of a target portion in a data object is received, wherein the target portion has reference content. Based on the target portion in the data object and at least a portion of the reference content, a target vectorized representation corresponding to the target portion is generated. The target vectorized representation is stored in a knowledge base and used to use at least one of the following as a result of a query for the data object: at least a portion of the target portion, at least a portion of the reference content.

[0050] In various embodiments of the present disclosure, when an application creator generates a vectorized representation of a target portion of a data object, it can simultaneously generate a vectorized representation of the referenced content within that portion and store it in the knowledge base. In this way, the application creator can batch-store vectorized representations of referenced content in the knowledge base, efficiently expanding the knowledge base's knowledge base. This can advantageously improve the quality of query results provided to end users.

[0051] Some example embodiments of the present disclosure will be described in detail below with reference to the examples in the accompanying drawings. It should be understood that the pages shown in the accompanying drawings are merely examples, and a variety of page designs may exist. The various graphical elements in a page may have different arrangements and different visual representations, one or more elements may be omitted or replaced, and one or more other elements may also be present. The embodiments of the present disclosure are not limited in this respect.

[0052] The following describes example embodiments of the present disclosure with reference to the accompanying drawings. For discussion purposes, the following examples are described from the perspective of an application management platform, such as application management platform 110 shown in FIG1 . The pages presented by application management platform 110 can be presented via a terminal device of user 105 , and user input can be received via the terminal device of user 105 .

[0053] Figure 2 shows a schematic diagram of transferring data to a knowledge base according to some embodiments of the present disclosure. As shown in Figure 2, a question-and-answer function 210 can be deployed on the application management platform 110. The question-and-answer function 210 recalls query results that match the terminal user's query based on the vectorized representation of the data. The data management platform 220 can be part of the application management platform 110, or it can be independent of the application management platform 110. Data tables 222 and structured data objects 224 (which are structured data) and unstructured data 228 (for example, documents, web pages, etc.) are maintained in the data management platform 220. Therefore, it is necessary to vectorize the data tables 222, structured data objects 224, and unstructured data 228. The vectorized representations corresponding to the data tables 222, data objects 224, and unstructured data 228 are then stored in the knowledge base 226. The question-and-answer function 210 returns the query results to the terminal user by calling the knowledge base 226 that stores the vectorized representations. The data objects described in this disclosure may include data tables 222 , data objects 224 , and unstructured data 228 .

[0054] The application management platform 110 receives a selection of a target portion in a data object, where the target portion has referenced content. The data object may be a data table 222, as shown in FIG. 2 , a structured data object 224, or unstructured data 228 (e.g., various documents). The following description primarily uses a data table as an example. However, it should be understood that the embodiments described with reference to a data table can also be applied to other types of data, such as unstructured data.

[0055] In some embodiments, the target portion includes the entire data object or a portion of the data in the data object. For example, if the data object is a data table, the target portion may be all fields in the data table, or a portion of the fields. If the data object is another type of file, the target portion may be the entire file, or a portion of a chapter or paragraph of the file.

[0056] The application management platform 110 may generate a target vectorized representation corresponding to the target portion based on the target portion in the data object and at least a portion of the referenced content.

[0057] In some embodiments, the data object includes a data table, and in response to the data table being selected for vector generation, the application management platform 110 presents fields in the data table and receives a selection of at least one field in the data table.

[0058] FIG3 illustrates an example of a page 300 for selecting fields in a data table, according to some embodiments of the present disclosure. Page 300 may be presented on a device of user 105. As shown in FIG3 , page 300 includes at least a data table selection area 310, a field selection area 320, and a selected fields area 330. For example, after user 105 selects a product information table for vector generation in data table selection area 310, the various fields in the product information table may be presented in select field area 310. User 105 may trigger selection controls 322, 324, and 326 to add the fields corresponding to these selection controls to selected fields area 330.

[0059] In some embodiments, the application management platform 110 can determine the target data entry in the data table based on the selected fields. For example, if the selected fields in the product information data table are product name and product review, and the field value of the product review field contains reference content, then the target data entry includes the field value of the product name field and the field value of the product review field, and the field value of the product review field indicates the reference content. The reference content here can include documents of a preset type, knowledge records in other knowledge bases, etc.

[0060] In some embodiments, upon receiving a selection of a target portion of the data object, the application management platform 110 may present an expanded prompt for the target portion to indicate that the target portion has referenced content. Subsequently, upon receiving an expanded confirmation of at least a portion of the referenced content, the application management platform 110 may generate a target vectorized representation corresponding to the target portion based on the target portion and at least a portion of the referenced content. The target portion of the data object may have multiple referenced contents (e.g., multiple reference links), and the user 105 may select some of the referenced contents to generate a target vectorized representation corresponding to the target portion.

[0061] In some embodiments, in response to at least one field being selected in a data table, the application management platform 110 presents an extended prompt for one or more of the at least one field, prompting that the field values ​​of the one or more fields indicate reference content. Continuing with FIG3 , an extended prompt for one or more of the selected fields is also presented within the selected field area 330. For example, the product description field has an extended prompt control 340 corresponding to it, and the product-specific knowledge space ID field has an extended prompt control 342 corresponding to it, prompting that the field values ​​of the product description field and the product-specific knowledge space ID field indicate reference content.

[0062] After determining the target data entry, the application management platform 110 may generate a target vectorized representation of the target data entry based on the field value of at least one field in the target data entry and at least a portion of the referenced content.

[0063] In some embodiments, if confirmation of the expansion prompt for a first field among the one or more fields is received, the application management platform 110 generates the target vectorized representation based on the field value of at least one field and the reference content indicated by the field value of the first field. For example, with continued reference to FIG3 , if the user 105 triggers the confirmation control 350, the application management platform 110 may generate the target vectorized representation.

[0064] In some embodiments, if a second field in the at least one field is selected, the application management platform 110 provides options for one or more reference content types based on the field type of the second field. If one or more reference content types are selected, the application management platform 110 determines the reference content indicated by the field value of the second field in the target data entry based on the selected reference content type.

[0065] For example, referring to Figure 3 , when user 105 triggers the extended prompt control 340, a page for selecting the reference content type for the product description field may pop up, as shown in Figure 4 . Figure 4 illustrates an example of page 400 for selecting the reference content type for a text field, according to some embodiments of the present disclosure. On page 400 , the reference content type for the product description field is document. User 105 can trigger select control 410 to select cloud document as the reference content indicated by the field value of the product description field. For another example, referring to Figure 3 , when user 105 triggers the extended prompt control 342, a page for selecting the reference content type for the product-specific knowledge space ID field may pop up, as shown in Figure 5 . Figure 5 illustrates an example of page 500 for selecting the reference content type for a numeric field, according to some embodiments of the present disclosure. On page 500 , the reference content type for the product-specific knowledge space ID field is knowledge base A or knowledge base B. User 105 can trigger select controls 510 or 512 to select the reference content indicated by the field value of the product-specific knowledge space ID field as knowledge base A or knowledge base B. The user 105 can also trigger the selection control 514 to choose not to cite other contents. In this way, the application creates a reference content that the user can flexibly select the field value to indicate, so that the knowledge base learns different types of reference content based on the user's selection.

[0066] In some embodiments, the application management platform 110 provides options for one or more document types in response to the second field being of text type. For example, the field value of the product description field is text, so the field type is text. Referring to FIG4 , for a text type field, the application management platform 110 provides document type options.

[0067] In some embodiments, the application management platform 110 provides options for one or more knowledge types in response to the second field being a numeric type. For example, the field value of the product-specific knowledge space ID is a numeric value, so the field type is a numeric type. Referring to Figure 5 , for a numeric field, the application management platform 110 provides options for Knowledge Base A and Knowledge Base B.

[0068] After generating the target vectorized representation, the application management platform 110 can store the target vectorized representation in a knowledge base (e.g., knowledge base 226) for use in queries against the knowledge base as the result of the query: at least a portion of the target data entry, at least a portion of the referenced content. Vectorizing the referenced content in the field value and storing it in the knowledge base can be considered extended learning. When a query initiated by user 145 is received, information representing the referenced content is also provided to the machine learning model so that the machine learning model can better understand the user's intent and provide a more accurate answer.

[0069] When the application management platform 110 receives a query against the knowledge base initiated by the user 145, it can return at least a portion of the target data entry to the user 145 as the result of the query. Since the user 145 may not have access rights to the referenced content, the application management platform 110 can return at least a portion of the referenced content (for example, the referenced content to which the user 145 has access rights) to the user 145 as the result of the query. Figure 6 shows an example of a page 600 that displays the results of a query according to some embodiments of the present disclosure. The page 600 includes at least a query area 610 and an answer area 620. The answer area 620 includes a text area 621 and a reference area 622. The text area 621 presents at least a portion of the target data entry and at least a portion of the referenced content, and the reference area 622 presents the source of the referenced content.

[0070] In some embodiments, the data table includes multiple data entries under at least one field. If at least one field is selected, the vectorized representations corresponding to the multiple data entries are stored in the knowledge base. The fields in the data table can be understood as columns in the data table, and the data entries in the data table can be understood as rows in the data table. For example, a product information data table can include information on product A, product B, and product C, then the product information data table includes 3 data entries under at least one field (i.e., data entry for product A, data entry for product B, and data entry for product C). For example, if the product name field and the product description field are selected, then the vectorized representation corresponding to the data entry for product A (i.e., the field value of the product name field of product A, the field value and reference content of the product description field of product A) is stored in the knowledge base. Similarly, the vectorized representations corresponding to the data entry for product B and the data entry for product C are also stored in the knowledge base.

[0071] In some embodiments, the application management platform 110 can display the learning status of references to various fields in a data table. Figure 7 shows an example of a page 700 showing the learning status of references to various fields in a data table by a knowledge base, according to some embodiments of the present disclosure. On page 700, some fields have completed learning, some are in the process of learning, and some have failed learning. This allows the user creating the application to understand the overall learning status of the knowledge base.

[0072] After storing the target vectorized representation in the knowledge base, the application management platform 110 can receive a query from a user 145 regarding a data object and determine a target vectorized representation matching the query from the knowledge base. The target vectorized representation is generated based on the target portion of the data object and at least a portion of the referenced content of the target portion. The application management platform 110 can then determine a result of the query based on the target vectorized representation. The result of the query indicates at least one of the following: at least a portion of the target portion and at least a portion of the referenced content.

[0073] In some embodiments, a machine learning model (e.g., model 155) can be used to determine a target vectorized representation from a knowledge base. For example, based on a query for a data object, the application management platform 110 can provide first information indicating at least a portion of the data object to the machine learning model, and obtain second information indicating the target vectorized representation from the machine learning model. The machine learning model can determine a vectorized representation associated with the query from the knowledge base.

[0074] In some embodiments, the query result indicates at least a portion of the referenced content, and the application management platform 110 may further present a message corresponding to the query result, the message including access information corresponding to the at least a portion of the referenced content. If the query result indicates at least a portion of the referenced content, the information corresponding to the query result presented by the application management platform 110 may include access information (e.g., a link) corresponding to the at least a portion of the referenced content.

[0075] In some embodiments, the target portion includes the entirety of the data object, or a portion of the data in the data object. For example, when the data object is a file of another type, the target portion may be the entirety of the file, or a portion of a section of the file.

[0076] In some embodiments, the data object includes a data table, and the target portion includes at least one selected field in the data table. For example, when the data object is a data table, the target portion can be all fields in the data table or at least one selected field.

[0077] In some embodiments, the data table includes multiple data entries under at least one field, and if at least one field is selected, the vectorized representations corresponding to the multiple data entries are stored in the knowledge base. The fields in the data table can be understood as columns in the data table, and the data entries in the data table can be understood as rows in the data table. For example, a product information data table can include information on product A, product B, and product C, then the product information data table includes 3 data entries under at least one field (i.e., data entry for product A, data entry for product B, and data entry for product C). For example, if the product name field and the product description field are selected, then the vectorized representation corresponding to the data entry for product A (i.e., the field value of the product name field of product A, the field value of the product description field of product A, and the reference content) is stored in the knowledge base. Similarly, the vectorized representations corresponding to the data entry for product B and the data entry for product C are also stored in the knowledge base.

[0078] FIG8A shows a flow chart of a process 800 of data processing according to some embodiments of the present disclosure. The process 800 may be implemented at the application management platform 110. The process 800 is described below with reference to FIG8A.

[0079] At block 810 , the application management platform 110 receives a selection of a target portion in a data object, the target portion having reference content.

[0080] In block 820 , the application management platform 110 generates a target vectorized representation corresponding to the target portion based on the target portion in the data object and at least a portion of the referenced content.

[0081] In block 830 , the application management platform 110 stores the target vectorized representation in the knowledge base for use in a query on the data object to use at least one of the following as a query result: at least a portion of the target portion, at least a portion of the referenced content.

[0082] In some embodiments, the target portion includes the entirety of the data object, or a portion of the data in the data object.

[0083] In some embodiments, generating a target vectorized representation includes: in response to receiving a selection of a target portion in a data object, presenting an extended prompt for the target portion to indicate that the target portion has referenced content; and in response to receiving an extended confirmation of at least a portion of the referenced content, generating a target vectorized representation corresponding to the target portion based on the target portion and at least a portion of the referenced content.

[0084] In some embodiments, the data object includes a data table, and receiving a selection of a target portion in the data object includes: in response to the data table being selected for vector generation, presenting fields in the data table; and receiving a selection of at least one field in the data table.

[0085] In some embodiments, process 800 further includes: in response to at least one field in the data table being selected, presenting an expanded hint for one or more fields in the at least one field to hint that field values ​​of the one or more fields indicate reference content.

[0086] In some embodiments, generating a target vectorized representation includes: in response to receiving confirmation of an extension hint for a first field among one or more fields, generating a target vectorized representation based on a field value of at least one field and a reference content indicated by the field value of the first field.

[0087] In some embodiments, process 800 also includes: in response to a second field in at least one field being selected, providing options for one or more reference content types based on the field type of the second field; receiving a selection of one or more reference content types; and determining the reference content indicated by the field value of the second field in the target data entry based on the selected reference content type.

[0088] In some embodiments, providing options for one or more reference content types includes at least one of the following: in response to the field type of the second field being a text type, providing options for one or more document types; and in response to the field type of the second field being a numeric type, providing options for one or more knowledge types.

[0089] In some embodiments, the data table includes a plurality of data entries under at least one field, and in response to at least one field being selected, vectorized representations corresponding to the plurality of data entries are stored in the knowledge base.

[0090] 8B shows a flowchart of another process 850 of data processing according to some embodiments of the present disclosure. Process 850 may be implemented at the application management platform 110. Process 850 is described below with reference to FIG8B.

[0091] At block 860 , the application management platform 110 receives a query for a data object.

[0092] In block 870 , the application management platform 110 determines a target vectorized representation matching the query from the knowledge base, where the target vectorized representation is generated based on a target portion in the data object and at least a portion of a reference content of the target portion.

[0093] In block 880 , the application management platform 110 determines a result of the query based on the target vectorized representation, where the result of the query indicates at least one of the following: at least a portion of the target portion, and at least a portion of the referenced content.

[0094] In some embodiments, the result of the query indicates at least a portion of the reference content, and process 850 further includes: presenting a message corresponding to the result of the query, the message including access information corresponding to the at least a portion of the reference content.

[0095] In some embodiments, the target portion includes the entirety of the data object, or a portion of the data in the data object.

[0096] In some embodiments, the data object includes a data table, and the target portion includes at least one selected field in the data table.

[0097] In some embodiments, the data table includes a plurality of data entries under at least one field, and in response to at least one field being selected, vectorized representations corresponding to the plurality of data entries are stored in the knowledge base.

[0098] In some embodiments, determining a target vectorized representation that matches the query from a knowledge base includes: providing first information indicating at least a portion of a data object to a machine learning model based on the query; and obtaining second information indicating the target vectorized representation from the machine learning model.

[0099] 9A shows a schematic structural block diagram of a data processing apparatus 900 according to some embodiments of the present disclosure. Apparatus 900 may be implemented in or included in application management platform 110. Each module / component in apparatus 900 may be implemented by hardware, software, firmware, or any combination thereof.

[0100] As shown in the figure, the apparatus 900 includes a selection receiving module 910 configured to receive a selection of a target portion in a data object, where the target portion has reference content.

[0101] The apparatus 900 further includes a target vectorized representation generating module 920 configured to generate a target vectorized representation corresponding to the target portion based on the target portion in the data object and at least a portion of the referenced content.

[0102] The device 900 also includes a target vectorized representation storage module 930, which is configured to store the target vectorized representation in a knowledge base, for using at least one of the following as a query result in a query for a data object: at least a part of the target part, at least a part of the referenced content.

[0103] In some embodiments, the target portion includes the entirety of the data object, or a portion of the data in the data object.

[0104] In some embodiments, the target vectorized representation generation module 920 includes an extended confirmation receiving module, which is configured to, in response to receiving a selection of a target part in a data object, present an extended prompt for the target part to indicate that the target part has referenced content; and in response to receiving an extended confirmation of at least a part of the referenced content, generate a target vectorized representation corresponding to the target part based on the target part and at least a part of the referenced content.

[0105] In some embodiments, the data object includes a data table, and the selection receiving module 910 includes a field presenting module configured to present fields in the data table in response to the data table being selected for vector generation; and receive a selection of at least one field in the data table.

[0106] In some embodiments, the device 900 also includes an extended prompt presentation module, which is configured to present an extended prompt for one or more fields in at least one field in response to at least one field in the data table being selected, so as to prompt that the field values ​​of one or more fields indicate reference content.

[0107] In some embodiments, the target vectorized representation generation module 920 is further configured to generate a target vectorized representation based on a field value of at least one field and a reference content indicated by the field value of the first field in response to receiving confirmation of an extension hint for a first field among the one or more fields.

[0108] In some embodiments, the device 900 also includes a reference content determination module, which is configured to provide options for one or more reference content types based on the field type of the second field in response to the second field in at least one field being selected; receive a selection of one or more reference content types; and determine the reference content indicated by the field value of the second field in the target data entry based on the selected reference content type.

[0109] In some embodiments, the reference content determination module is further configured to perform at least one of the following: in response to the field type of the second field being a text type, provide options for one or more document types; and in response to the field type of the second field being a numerical type, provide options for one or more knowledge types.

[0110] In some embodiments, the data table includes a plurality of data entries under at least one field, and in response to at least one field being selected, vectorized representations corresponding to the plurality of data entries are stored in the knowledge base.

[0111] 9B shows a schematic structural block diagram of a data processing apparatus 950 according to some embodiments of the present disclosure. Apparatus 950 may be implemented in or included in the application management platform 110. Each module / component in apparatus 950 may be implemented by hardware, software, firmware, or any combination thereof.

[0112] As shown in the figure, the apparatus 950 includes a query receiving module 960 configured to receive a query for a data object.

[0113] The device 950 also includes a target vectorized representation determination module 970, which is configured to determine a target vectorized representation matching the query from the knowledge base, where the target vectorized representation is generated based on a target part in the data object and at least a part of the reference content of the target part.

[0114] The apparatus 950 further includes a query result determination module 980 configured to determine a query result based on the target vectorized representation, the query result indicating at least one of the following: at least a portion of the target portion, at least a portion of the referenced content.

[0115] In some embodiments, the query result indicates at least a portion of the referenced content, and device 950 further includes a query result presentation module configured to present a message corresponding to the query result, the message including access information corresponding to at least a portion of the referenced content.

[0116] In some embodiments, the target portion includes the entirety of the data object, or a portion of the data in the data object.

[0117] In some embodiments, the data object includes a data table, and the target portion includes at least one selected field in the data table.

[0118] In some embodiments, the data table includes a plurality of data entries under at least one field, and in response to at least one field being selected, vectorized representations corresponding to the plurality of data entries are stored in the knowledge base.

[0119] In some embodiments, the target vectorized representation determination module 970 is further configured to provide first information indicating at least a portion of the data object to the machine learning model based on the query; and obtain second information indicating the target vectorized representation from the machine learning model.

[0120] FIG10 shows a block diagram of an electronic device 1000 in which one or more embodiments of the present disclosure may be implemented. It should be understood that the electronic device 1000 shown in FIG10 is merely exemplary and should not be construed as limiting the functionality and scope of the embodiments described herein. The electronic device 1000 shown in FIG10 may include or be implemented as the application management platform 110 of FIG1 , the device 900 of FIG9A , or the device 950 of FIG9B .

[0121] As shown in FIG10 , electronic device 1000 is in the form of a general electronic device. Components of electronic device 1000 may include, but are not limited to, one or more processors or processing units 1010, memory 1020, storage device 1030, one or more communication units 1040, one or more input devices 1050, and one or more output devices 1060. Processing unit 1010 may be a real or virtual processor and is capable of performing various processes according to a program stored in memory 1020. In a multi-processor system, multiple processing units execute computer-executable instructions in parallel to enhance the parallel processing capabilities of electronic device 1000.

[0122] The electronic device 1000 typically includes a plurality of computer storage media. Such media can be any accessible media that is accessible to the electronic device 1000, including but not limited to volatile and non-volatile media, removable and non-removable media. The memory 1020 can be a volatile memory (e.g., registers, cache, random access memory (RAM)), a non-volatile memory (e.g., read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. The storage device 1030 can be a removable or non-removable medium and can include a machine-readable medium, such as a flash drive, a disk, or any other medium that can be used to store information and / or data and can be accessed within the electronic device 1000.

[0123] The electronic device 1000 may further include additional removable / non-removable, volatile / non-volatile storage media. Although not shown in FIG. 10 , a disk drive for reading from or writing to a removable, non-volatile disk (e.g., a “floppy disk”) and an optical drive for reading from or writing to a removable, non-volatile optical disk may be provided. In these cases, each drive may be connected to a bus (not shown) by one or more data media interfaces. The memory 1020 may include a computer program product 1025 having one or more program modules configured to perform various methods or actions of various embodiments of the present disclosure.

[0124] The communication unit 1040 enables communication with other electronic devices via a communication medium. Additionally, the functions of the components of the electronic device 1000 can be implemented as a single computing cluster or multiple computing machines that can communicate via a communication connection. Thus, the electronic device 1000 can operate in a networked environment using logical connections to one or more other servers, network personal computers (PCs), or other network nodes.

[0125] Input device 1050 may be one or more input devices, such as a mouse, keyboard, or trackball. Output device 1060 may be one or more output devices, such as a display, a speaker, or a printer. Electronic device 1000 may also communicate with one or more external devices (not shown) via communication unit 1040 as needed, such as storage devices, display devices, or the like, with one or more devices that allow a user to interact with electronic device 1000, or with any device that allows electronic device 1000 to communicate with one or more other electronic devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface (not shown).

[0126] According to an exemplary implementation of the present disclosure, a computer-readable storage medium is provided, on which computer-executable instructions are stored, wherein the computer-executable instructions are executed by a processor to implement the method described above. According to an exemplary implementation of the present disclosure, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, and the computer-executable instructions are executed by a processor to implement the method described above.

[0127] Various aspects of the present disclosure are described herein with reference to flowcharts and / or block diagrams of methods, apparatuses, devices, and computer program products implemented according to the present disclosure. It should be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0128] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, such that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device is generated that implements the functions / actions specified in one or more blocks in the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium, where these instructions cause the computer, programmable data processing device, and / or other device to operate in a specific manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing various aspects of the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0129] Computer-readable program instructions can be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0130] The flow charts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple implementations of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a part for a module, program segment or instruction, and a part for a module, program segment or instruction comprises one or more executable instructions for realizing the logical function of the specification. In some alternative implementations, the functions marked in the box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be realized by a special hardware-based system that performs the function or action of the specification, or can be realized by a combination of special hardware and computer instructions.

[0131] While various implementations of the present disclosure have been described above, the foregoing description is intended to be illustrative, not exhaustive, and not limited to the disclosed implementations. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described implementations. The terminology used herein is selected to best explain the principles of the implementations, their practical applications, or improvements to existing technologies, or to enable others skilled in the art to understand the various implementations disclosed herein.

Claims

1. A method for data processing, comprising: receiving a selection of a target portion in a data object, the target portion having reference content; Based on the target portion in the data object and at least a portion of the referenced content, generate a target vectorized representation corresponding to the target portion; as well as The target vectorized representation is stored in a knowledge base, and is used to use at least one of the following as a result of the query in a query for the data object: at least a part of the target part, at least a part of the reference content. 2 . The method according to claim 1 , wherein the target portion includes the entirety of the data object, or a portion of data in the data object.

3. The method according to claim 1, wherein generating the target vectorized representation comprises: In response to receiving a selection of a target portion in the data object, presenting an expanded prompt for the target portion to prompt that the target portion has the reference content; as well as In response to receiving an extended confirmation of at least a portion of the reference content, a target vectorized representation corresponding to the target portion is generated based on the target portion and the at least a portion of the reference content.

4. The method of claim 1 , wherein the data object comprises a data table, and wherein receiving a selection of a target portion in the data object comprises: In response to the data table being selected for vector generation, presenting fields in the data table; as well as A selection of at least one field in the data table is received.

5. The method according to claim 4, further comprising: In response to the at least one field in the data table being selected, an extended prompt for the one or more fields in the at least one field is presented to prompt that field values ​​of the one or more fields indicate reference content.

6. The method according to claim 5, wherein generating the target vectorized representation comprises: In response to receiving confirmation of the extension hint for a first field among the one or more fields, the target vectorized representation is generated based on a field value of the at least one field and reference content indicated by the field value of the first field.

7. The method according to claim 4, further comprising: In response to a second field of the at least one field being selected, providing options for one or more reference content types based on a field type of the second field; receiving a selection of the one or more reference content types; as well as Determine the field value of the second field in the target data entry according to the selected reference content type. The reference content indicated.

8. The method of claim 7, wherein providing options for one or more reference content types comprises at least one of the following: In response to the field type of the second field being a text type, providing options for one or more document types; and In response to the field type of the second field being a numerical type, options for one or more knowledge types are provided.

9. The method according to claim 4, wherein the data table includes multiple data entries under the at least one field, and in response to the at least one field being selected, vectorized representations corresponding to the multiple data entries are stored in the knowledge base.

10. A method for data processing, comprising: receiving queries for data objects; Determining a target vectorized representation matching the query from a knowledge base, wherein the target vectorized representation is generated based on a target portion in the data object and at least a portion of a reference content of the target portion; as well as A result of the query is determined based on the target vectorized representation, the result of the query indicating at least one of the following: at least a portion of the target portion, at least a portion of the referenced content.

11. The method of claim 10, wherein the result of the query indicates at least a portion of the reference content, the method further comprising: A message corresponding to the result of the query is presented, wherein the message includes access information corresponding to the at least a portion of the referenced content.

12. The method according to claim 10, wherein the target portion includes the entirety of the data object, or a portion of data in the data object.

13. The method of claim 10, wherein the data object comprises a data table, and the target portion comprises at least one selected field in the data table.

14. The method according to claim 13, wherein the data table includes a plurality of data entries under the at least one field, and in response to the at least one field being selected, vectorized representations corresponding to the plurality of data entries are stored in the knowledge base.

15. The method according to claim 10, wherein determining a target vectorized representation matching the query from a knowledge base comprises: providing first information indicative of at least a portion of the data object to a machine learning model based on the query; as well as Second information indicating the target vectorized representation is obtained from the machine learning model.

16. A data processing device, comprising: A selection receiving module is configured to receive a selection of a target portion in a data object, wherein the target portion has There are quoted contents; A target vectorized representation generation module, configured to generate a target vectorized representation corresponding to the target portion based on the target portion in the data object and at least a portion of the referenced content; as well as A target vectorized representation storage module is configured to store the target vectorized representation in a knowledge base for use in a query against the data object with at least one of the following as a query result: at least a portion of the target portion, at least a portion of the referenced content.

17. A data processing device, comprising: A query receiving module, configured to receive a query for a data object; a target vectorized representation determination module, configured to determine a target vectorized representation matching the query from a knowledge base, wherein the target vectorized representation is generated based on a target portion in the data object and at least a portion of a reference content of the target portion; and A query result determination module is configured to determine a result of the query based on the target vectorized representation, wherein the result of the query indicates at least one of the following: at least a portion of the target portion, and at least a portion of the referenced content.

18. An electronic device, comprising: at least one processing unit; as well as At least one memory, the at least one memory being coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions causing the electronic device to perform the method according to any one of claims 1 to 15 when executed by the at least one processing unit.

19. A computer-readable storage medium having a computer program stored thereon, wherein the computer program can be executed by a processor to implement the method according to any one of claims 1 to 15.

20. A computer program product tangibly stored in a computer storage medium and comprising computer executable instructions which, when executed by a device, cause the device to perform the method according to any one of claims 1-15.

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