Table data processing method and device, computer equipment, storage medium and program product

Abstract

The invention provides a table data processing method and device, computer equipment, a storage medium and a program product. The method comprises the steps of displaying a first page in response to a data association request for a first field of a first data row in a first data table; wherein the first page comprises a plurality of second data lines of a second data table associated with the first field and a recommendation control; in response to a trigger instruction for the recommendation control, displaying a second data line of the plurality of recommendation data lines corresponding to the first field on the first page; wherein the plurality of recommended data rows are selected from the second data table, and the plurality of recommended data rows are associated with the first data row. According to the table data processing method and device, the computer equipment, the storage medium and the program product provided by the invention, the difficulty that a user finds a data line which the user wants to associate can be reduced to a certain extent.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technologies, and particularly to a method and apparatus for processing tabular data, a computer device, a storage medium, and a program product. Background Art

[0002] With the continuous development of Internet technologies, many tasks can be completed intelligently. For example, a table can be created and maintained through collaborative office software.

[0003] In related technologies, a certain field of a certain data row in a data table can be associated with one or more data rows of another data table, so that information of the other data table associated therewith can be conveniently viewed in this data table.

[0004] However, the inventors of the present disclosure have found that in related technologies, the process of performing an association operation in a data table is not simple enough. Summary of the Invention

[0005] The present disclosure provides a method and apparatus for processing tabular data, a computer device, a storage medium, and a program product to solve or partially solve the above problems.

[0006] In a first aspect of the present disclosure, a method for processing tabular data is provided, including:

[0007] In response to a data association request for a first field of a first data row in a first data table, a first page is displayed; wherein, the first page includes a plurality of second data rows of a second data table associated with the first field and a recommendation control;

[0008] In response to a trigger instruction for the recommendation control, a plurality of recommended data rows corresponding to the first field are displayed on the first page; wherein, the plurality of recommended data rows are selected from the second data rows of the second data table, and the plurality of recommended data rows are associated with the first data row.

[0009] In a second aspect of the present disclosure, an apparatus for processing tabular data is provided, including:

[0010] A first display module configured to: in response to a data association request for a first field of a first data row in a first data table, display a first page; wherein, the first page includes a plurality of second data rows of a second data table associated with the first field and a recommendation control;

[0011] A second display module configured to: in response to a trigger instruction for the recommendation control, display a plurality of recommended data rows corresponding to the first field on the first page; wherein, the plurality of recommended data rows are selected from the second data rows of the second data table, and the plurality of recommended data rows are associated with the first data row.

[0012] In a third aspect of the present disclosure, a computer device is provided, including one or more processors, a memory; and one or more programs, where the one or more programs are stored in the memory and executed by the one or more processors, and the one or more programs include instructions for executing the method described in the first aspect.

[0013] In a fourth aspect of the present disclosure, a non-volatile computer-readable storage medium containing a computer program is provided. When the computer program is executed by one or more processors, the one or more processors are caused to execute the method described in the first aspect.

[0014] In a fifth aspect of the present disclosure, a computer program product is provided, including one or more computer programs, where when the one or more computer programs are executed by one or more processors, the method described in the first aspect is implemented.

[0015] The table data processing method, apparatus, computer device, storage medium, and program product provided in the embodiments of the present disclosure recommend a recommended data row matching the first data row to the user through a recommendation function when the user uses the association function of the table, reducing the difficulty for the user to find the data row they want to associate. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present disclosure or related technologies, the following will briefly introduce the drawings required for use in the embodiments or related technology descriptions. Obviously, the drawings in the following description are only the embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 Shows a schematic diagram of an exemplary system provided by the embodiments of the present disclosure.

[0018] Figure 2A Shows a schematic diagram of an exemplary page according to an embodiment of the present disclosure.

[0019] Figure 2B Shows another schematic diagram of an exemplary page according to an embodiment of the present disclosure.

[0020] Figure 2C Shows yet another schematic diagram of an exemplary page according to an embodiment of the present disclosure.

[0021] Figure 2D Shows yet another schematic diagram of an exemplary page according to an embodiment of the present disclosure.

[0022] Figure 2EShows another schematic diagram of an exemplary page according to an embodiment of the present disclosure.

[0023] Figure 2F Shows another schematic diagram of an exemplary page according to an embodiment of the present disclosure.

[0024] Figure 2G Shows another schematic diagram of an exemplary page according to an embodiment of the present disclosure.

[0025] Figure 3A Shows a schematic flowchart of an exemplary method for obtaining recommended data rows according to an embodiment of the present disclosure.

[0026] Figure 3B Shows a schematic flowchart of an exemplary method for obtaining candidate data rows according to an embodiment of the present disclosure.

[0027] Figure 3C Shows a schematic flowchart of an exemplary method for establishing a vector database according to an embodiment of the present disclosure.

[0028] Figure 3D Shows a schematic diagram of an exemplary page for configuring a data range according to an embodiment of the present disclosure.

[0029] Figure 4 Shows a schematic flowchart of an exemplary method provided by an embodiment of the present disclosure.

[0030] Figure 5 Shows a schematic diagram of the hardware structure of an exemplary computer device provided by an embodiment of the present disclosure.

[0031] Figure 6 Shows a schematic diagram of an exemplary device provided by an embodiment of the present disclosure. Detailed implementation manners

[0032] To make the objectives, technical solutions, and advantages of the present disclosure clearer and more understandable, the present disclosure will be further described in detail below with reference to specific embodiments and the accompanying drawings.

[0033] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should have the ordinary meanings understood by those of ordinary skill in the field to which the present disclosure belongs. The "first", "second" and similar terms used in the embodiments of the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. The terms such as "including" or "comprising" mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0034] It can be understood that before using the technical solutions of the various embodiments of the present disclosure, the types, usage scopes, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.

[0035] For example, when a user's active request is received, a prompt message is sent to the user to clearly prompt the user that the operation requested by the user will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, an application program, a server, or a storage medium that performs the operations of the technical solutions of the present disclosure according to the prompt message.

[0036] As an optional but non-limiting implementation manner, the manner of sending a prompt message to the user in response to receiving the user's active request may be, for example, in the form of a pop-up window, and the prompt message may be presented in text in the pop-up window. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0037] It can be understood that the above process of notifying and obtaining the user's authorization is only illustrative and does not limit the implementation manner of the present disclosure, and other manners that meet the relevant laws and regulations can also be applied to the implementation manner of the present disclosure.

[0038] Figure 1 FIG. shows a schematic diagram of an exemplary system 100 provided by the embodiments of the present disclosure.

[0039] As Figure 1As shown, the system 100 can be used to implement functions such as the creation and maintenance of tables, and may include terminal devices 102A, 102B, a server 106, and a database server 108. A medium (e.g., a network) providing a communication link may be included between the terminal devices 102A and the server 106 and the database server 108. The network may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0040] Various application programs (APPs) or software can be installed on the terminal devices 102A, 102B. For example, collaborative office application programs or software, image processing application programs or software, video conferencing application programs or software, reading application programs or software, video application programs or software, social application programs or software, payment application programs or software, web browsers, and instant messaging tools, etc. In some embodiments, these application programs or software can all be used for the creation and maintenance of tables, etc.

[0041] The terminal devices 102A, 102B here can be hardware or software. When the terminal devices 102A, 102B are hardware, they can be various electronic devices or computer devices with a display screen, including but not limited to smartphones, tablets, e - book readers, MP3 players, laptop computers, and desktop computers, etc. When the terminal devices 102A, 102B are software, they can be installed in the above - listed electronic devices. It can be implemented as multiple software or software modules (e.g., used to provide distributed services), or can be implemented as a single software or software module. No specific limitation is made here.

[0042] The server 106 can be a server providing various services, such as a background server supporting various applications or software displayed on the terminal devices 102A, 102B. The database server 108 can also be a database server providing various services. It can be understood that when the relevant functions of the database server 108 can be implemented by the server 106, the database server 108 may not be set in the system 100.

[0043] The server 106 and the database server 108 here can also be hardware or software. When they are hardware, they can be implemented as a distributed server cluster composed of multiple servers, or can be implemented as a single server. When they are software, they can be implemented as multiple software or software modules (e.g., used to provide distributed services), or can be implemented as a single software or software module. No specific limitation is made here.

[0044] It should be noted that the table data processing method provided by the embodiments of the present disclosure can be executed by the terminal devices 102A and 102B or by the interaction of each device in the system 100. It should be understood that Figure 1 the numbers of the terminal devices, users, servers, and database servers in

[0045] are merely illustrative. According to the implementation requirements, there can be any number of terminal devices, users, servers, and database servers. In some exemplary scenarios, the user 104A or the user 104B can respectively create and maintain a table through a collaborative office software or application installed in the terminal device 102A or the terminal device 102B. Optionally, the user 104A and the user 104B can jointly maintain the same table. For example, view, add, modify, and delete data rows in the table. Optionally, the table can be a table for multi-dimensional management of a project and can include multiple data tables under multiple dimensions. Therefore, the table can further include multiple data tables. Each data table can be used to store data corresponding to its corresponding dimension and can have an association relationship with other data tables.

[0046] As an optional embodiment, the user 104A and / or the user 104B can also associate the fields of the data rows in the A data table of the table with the data rows in the B data table, so that the user 104A and / or the user 104B can view the information of the data rows in the B data table associated with the field in the A data table.

[0047] In some embodiments, the association can include unidirectional association and bidirectional association.

[0048] The unidirectional association can mean that some fields in the table support the unidirectional association function, that is, the data rows in the B data table are associated in the A data table. In this way, after the association is completed, the entire row information of the data row can be clicked and viewed in this field of the A data table, and further jump to the B data table associated with this field for viewing. In some embodiments, the fields of the unidirectional association can also be associated with the data rows in the current data table (i.e., the A data table).

[0049] The bidirectional association can mean that some fields in the table support the bidirectional association function. Using the bidirectional association fields, one or more data rows in the B data table can be associated in the A data table, and the associated data rows in the B data table will be automatically associated back to the corresponding data rows in the A data table. The user can directly view the data in the B data table in the A data table and can further jump to the B data table. Moreover, the user can also jump back to the A data table with one key from the B data table.

[0050] It can be seen that when user 104A and / or user 104B perform an association operation in the current data table, they need to first find the data rows to be associated in another data table, and then associate the two through the association operation. However, the inventors of the present disclosure found that when the number of data rows in another data table (for example, Table B) is very large, the user may need to continuously scroll through the data rows of the data table to find the data rows to be associated, and the operation is not simple enough.

[0051] In view of this, in the first aspect of the embodiments of the present disclosure, a method for processing tabular data is provided, which can solve or partially solve the above problems to a certain extent.

[0052] As mentioned above, user 104A and / or user 104B can use the collaborative office software or application installed in the terminal devices 102A and 102B to create and maintain a table.

[0053] Exemplarily, in the initial state, user 104A can use the terminal device 102A to open the collaborative office software or application, and further open the table to be maintained, or create a new table.

[0054] In some embodiments, the table may include multiple data tables in multiple dimensions. For example, the table may be an order and commodity statistics table, and thus may further include a data table for statistics of orders, a data table for statistics of commodities, and other related data tables, and so on.

[0055] Exemplarily, user 104A can further open one of the data tables for data maintenance. For example, in the table, the data table can be opened by triggering the corresponding label of the data table.

[0056] Figure 2A Shows a schematic diagram of an exemplary page 200 according to an embodiment of the present disclosure.

[0057] As Figure 2A shown, user 104A triggers the first data table, so that the first data table 202 can be displayed in page 200. The first data table 202 may further include multiple first data rows 2022. Exemplarily, the first data table 202 may be an order table for recording orders. In other words, each data row in the order table records an order. Therefore, the data rows in the data table can also be referred to as records.

[0058] In some embodiments, as Figure 2AAs shown in the figure, the first data table 202 may further include multiple fields, and each field may correspond to a type of attribute information of the first data row 2022. Taking an order table as an example, it may include multiple fields such as order number, order status, person in charge, business line, order placement time, product library, etc. By filling in the corresponding field information in each first data row 2022, a corresponding record of an order can be made.

[0059] Optionally, as Figure 2A shown in the figure, the page 200 may further include a field addition control 204. The user 104A can trigger this field addition control 204 to add a new field to the first data table 202, thereby enriching the content of the first data table 202.

[0060] In some embodiments, when a specific field supports a one-way association or a two-way association function, the user 104A can associate this specific field with a data row in another data table. Exemplarily, as Figure 2A shown in the figure, the product library field can be a field that can achieve a one-way association or a two-way association. Thus, the user 104A can perform an association operation for the product library field in the data row. Optionally, whether a field can be associated with other data tables, which data tables it can be associated with, and whether this association is a one-way association or a two-way association can all be pre-configured. Exemplarily, the product library field can be associated with a product table, so that corresponding data rows can be found from the product table and associated with the product library field of the first data table 202.

[0061] Exemplarily, the user 104A can generate a data association request by triggering (for example, clicking or double-clicking) the first field 2024 of the first data row 2022 of the first data table 202 in the page 200 (for example, Figure 2A the first row data row of the first data table in Figure 2A the cell corresponding to the product library field of the first data row 2022). Thus, in response to this data association request, the terminal device 102A can further display the first page 210, as Figure 2B shown in the figure.

[0062] In some embodiments, as Figure 2B shown in the figure, the first page 210 can be floatingly displayed above the page 200. Compared with operating by jumping to a new page, this embodiment can give the user 104A a feeling of performing data maintenance for the first data table 202 in the page 200, which is more in line with the user's habits and thus improves the user experience.

[0063] As Figure 2BAs shown, optionally, a second data table 212 associated with the first field 2024 may be further displayed in the first page 210, so that the user 104A can find the second data row 2122 of the second data table 212 that he wants to associate in the first page 210. Optionally, the association relationship between the second data table 212 and the first field 2024 may be pre-configured on the field corresponding to the first field 2024, so that when the first field 2024 is triggered, the content of the second data table 212 can be displayed on the first page 210. Exemplarily, the second data table 212 may be a product table for recording product information, and the associated field may be the product library field of the first data table 202.

[0064] As Figure 2B shown, the second data table 212 may include a plurality of second data rows 2122. When the display range of the first page 210 is not sufficient to display all the second data rows 2122 of the second data table 212, in some embodiments, a scroll bar 2124 may be displayed on one side of the second data table 212. The scroll bar 2124 is used to scroll the second data table 212 in the first direction (for example, the vertical direction of the first page 210), so that the user 104A can slide and view other second data rows 2122 in the second data table 212 by moving the scroll bar 2124, and the operation is relatively convenient.

[0065] In some embodiments, as Figure 2B shown, the first page 210 may further include a search bar 214, so that the user 104A can search for the second data row 2122 that he wants to associate in the second data table 212 by entering a search term in the search bar 214, thereby facilitating the user to find the second data row 2122 that he wants to associate more quickly. Optionally, the search bar 214 may be displayed at the top of the first page 210, so that the user 104A can more easily observe the search bar 214 and thus use it more conveniently.

[0066] It can be understood that when the number of second data rows 2122 of the second data table 212 is large, the first page 210 cannot fully display all the content of the second data table 212. In particular, when the number of second data rows 2122 of the second data table 212 is extremely large, the user 104A may have difficulty finding the second data row that he wants to associate. Even if the search bar 214 is used for searching, it may be impossible to search for a suitable result due to inaccurate search terms.

[0067] Therefore, in some embodiments of the present disclosure, as Figure 2BAs shown, a recommendation control 216 may also be displayed on the first page 210. In this way, the user 104A can obtain a recommended data row by using the recommendation function corresponding to the recommendation control 216, so that it is easier to find the second data row that the user wants to associate with.

[0068] In some embodiments, a display condition for whether the recommendation control 216 is displayed on the first page 210 may also be set, so that the recommendation control 216 is only displayed when the condition is met, making the page more concise. Optionally, when the number of the second data rows 2122 in the second data table 212 (for example, the total number of the second data rows 2122 in the second data table 212) is greater than or equal to a second number (for example, 10, 20, 50, etc.), the recommendation control 216 may be further displayed on the first page 210, as Figure 2B shown. In this way, when there are more second data rows 2122, providing the recommendation function by displaying the recommendation control 216 enables the user to more easily find the second data row that the user wants to associate with. It can be understood that the condition for displaying the recommendation control 216 may also be other conditions. For example, when the user 104A has difficulty finding the second data row 2122 that the user wants to associate with through searching or similar means, the recommendation control 216 may be displayed on the first page 210 so that the user 104A can more easily find the second data row 2122 that the user wants to associate with through the recommendation function. In some embodiments, when the number of the second data rows 2122 in the second data table 212 is less than the second number (for example, 10), the recommendation control 216 may not be displayed. At this time, since the number of the second data rows 2122 is small, the user 104A can easily find the second data row that the user wants to associate with among them. Therefore, the recommendation function can be omitted and the recommendation control 216 does not need to be displayed, thus keeping the content of the first page 210 concise.

[0069] In some embodiments, as Figure 2B shown, the display position of the recommendation control 216 may be an associated position of the search bar 214 (for example, adjacent to and below the search bar 214), so that the user 104A can more easily observe the recommendation control 216. In particular, when the user 104A uses the search function to search for the second data row and fails to obtain a suitable search result, it is more convenient to use the recommendation function.

[0070] Optionally, as Figure 2BAs shown, the recommendation control 216 is located between the search bar 214 and the multiple second data rows 2122. Or rather, when entering the first page 210, when the display condition of the recommendation control 216 is met, the search bar 214, the recommendation control 216, and the multiple second data rows 2122 are displayed on the first page 210 in the top-down arrangement order, so that the content arrangement of the first page 210 is more in line with user habits and improves the user experience.

[0071] As previously mentioned, the user 104A can search for the second data rows 2122 in the second data table 212 by using the search bar 214. Therefore, in some embodiments, after the first page 210 is displayed, when a search term (e.g., cap) is entered in the search bar 214, a search can be performed in the multiple second data rows 2122 of the second data table 212 (which can be all the second data rows included in the second data table 212) based on the search term, and the second data rows 2122 that match the search term are displayed, as Figure 2C shown. Optionally, when the user 104A starts entering a search term in the search bar 214, the search function can be triggered, so that as the search term entered by the user 104A changes, the corresponding search results can be displayed in real time in the first page 210 according to the information that appears in the search bar 214. Or, alternatively, after the user 104A enters the search term (e.g., cap) that he or she wants to enter completely in the search bar 214, the search function can be triggered by pressing the Enter key, and then the search results obtained based on the search term (e.g., cap) are displayed in the first page 210, so as to ensure that the search results are associated with the search term that the user wants to enter and improve the user experience.

[0072] Optionally, after the search is completed, as Figure 2C shown, an add control 2142 can also be displayed in the first page 210 for the user 104A to add a new second data row in the second data table 212 to enrich the content of the second data table 212. In particular, when there is no second data row that the user 104A wants to associate in the search results, the user 104A can trigger the add function corresponding to the add control 2142 to add a new second data row and associate the newly added second data row with the first field 2024 of the first data row 2022, without having to jump to the page of the second data table 212 to add, which is convenient for the user to use. Optionally, as Figure 2C shown, after the search is completed, the recommendation control 216 can also continue to be displayed in the first page 210, so that when the search results do not include the second data row that the user 104A wants to associate, the user 104A can directly use the recommendation function of the recommendation control 216 to obtain the recommended second data row to shorten the jump link of the recommendation function, without having to return to the initial state to use the recommendation function.

[0073] In some embodiments, after searching for the search term in the multiple second data rows of the second data table, if the second data table 212 does not include the second data row 2122 that matches the search term (e.g., top hat), information 2144 for prompting the user that there are no search results currently (e.g., "There are no relevant records. Please re-enter the keyword or add a new record") may be displayed on the first page 210, and the recommendation control 216 may continue to be displayed on the first page 210, as Figure 2D shown. In this way, when the user 104A does not find any search results based on the search term, the recommendation function of the recommendation control 216 can be directly used to obtain the recommended second data row to shorten the jump link of the recommendation function, without having to return to the initial state to use the recommendation function.

[0074] Optionally, after the search is completed, as Figure 2D shown, an add control 2146 may also be displayed on the first page 210 for the user 104A to add a new second data row to the second data table 212 to enrich the content of the second data table 212. In particular, when there are no search results, the user 104A can trigger the add function corresponding to the add control 2142 to add a new second data row and associate the newly added second data row with the first field 2024 of the first data row 2022, without having to jump to the page of the second data table 212 to add, which is convenient for the user to use.

[0075] Continuing to refer to Figure 2B , in some embodiments, the user 104A can use the recommendation function by triggering (e.g., clicking) the recommendation control 216. In response to the trigger instruction for the recommendation control 216, the terminal device 102A can display a plurality of recommended data rows 220 corresponding to the first field 2024 on the first page 210, as Figure 2E shown. Among them, the plurality of recommended data rows 220 may be the second data rows 2122 in the second data table 212, so that when the user 104A associates the first field 2024 with the recommended data row 220, the corresponding second data row 2122 in the second data table 212 can be associated with the first field 2024.

[0076] In some embodiments, the plurality of recommended data rows 220 may be associated with the first data row 2022, or rather, the recommended data row 220 is based on the first data row 2022 that needs to be associated currently (e.g., Figure 2AThe relevant information or data of the first row of data in the first data table 202 is used for recommendation, so that the recommended data row 220 is more suitable to be associated with the first data row 2022 that needs to be associated currently, and it also better meets the user's needs, thereby improving the user experience. In this way, when multiple recommended data rows 220 are displayed on the first page 210, these recommended data rows 220 may better meet the user's expectations, and thus help the user to more easily perform the association operation.

[0077] Optionally, as Figure 2E shown, the multiple recommended data rows 220 can be displayed between the search bar 214 and the multiple second data rows 2122, so that the multiple recommended data rows 220 can be more located at the upper part of the first page 210, which is more conducive to the user 104A to view and select. Optionally, since the recommended data rows 220 obtained based on the recommendation function are already displayed currently, the recommendation control 216 can be stopped from being displayed, making the display content of the first page 210 more concise.

[0078] In some embodiments, it may take some time to obtain the recommended data row 220. Therefore, as Figure 2F shown, in response to the trigger instruction for the recommendation control 216, the terminal device 102A can first display the information 230 (e.g., "Searching for matching records...") for prompting the user that the recommended data row is being obtained on the first page 210, so that after seeing the information 230, the user 104A can know that the recommended data row matching the first data row 2022 is being searched currently, and thus can wait patiently. Optionally, Figure 2F the page shown as such can be the page displayed during the waiting process for obtaining the recommended data row. After the waiting ends, the table corresponding to the recommended data row can be rendered, and then the page shown as Figure 2G shown can be displayed, so that a page displaying the table frame 240 can be inserted between the display of the recommended data row and the waiting display, avoiding the abrupt feeling of suddenly displaying the recommended data row. It can be understood that the rendering process may be very fast, Figure 2G and the page of

[0079] may not be easily observable by the user 104A, but it can still weaken the abrupt feeling to a certain extent.

[0079] Furthermore, when the terminal device 102A obtains the multiple recommended data rows 220, as Figure 2E shown, the multiple recommended data rows 220 corresponding to the first field 2024 can be displayed on the first page 210, so that the user can select the data row to be associated from them for the association operation.

[0080] In some embodiments of the present disclosure, a method for obtaining the recommended data row 220 can also be provided. As Figure 3AAs shown, the method may further include the following steps.

[0081] In step 302, obtain a plurality of candidate data rows associated with the first data row 2022 (e.g., Figure 2A the first row of data of the first data table 202).

[0082] In this step, first, a plurality of candidate data rows associated with the first data row 2022 (or the current data row, e.g., Figure 2A the first row of data of the first data table 202) can be found. Subsequently, after some processing and selection, the recommended data row 220 can be determined and displayed on the first page 210.

[0083] Since there is a certain degree of association between the candidate data rows and the first data row 2022, the candidate data rows may be the data rows that the user wants to associate. It can be understood that the manner of obtaining the candidate data rows associated with the first data row 2022 can be arbitrary. As long as there is an association between the two, the candidate data rows can be used for recommendation to the user.

[0084] In some embodiments, a plurality of candidate data rows associated with the first data row can be obtained by means of feature matching. As Figure 3B shown, the method may further include the following steps.

[0085] In step 3022, extract a plurality of first keywords from the first data row 2022 (or the current data row, e.g., Figure 2A the first row of data of the first data table 202).

[0086] In this step, a common keyword extraction algorithm can be used to extract the first keywords from the first data row 2022. Optionally, the keyword extraction algorithm can be the term frequency-inverse document frequency (TF-IDF) algorithm, graph-based ranking algorithms (e.g., TextRank algorithm, PageRank algorithm), etc. As Figure 2A shown, since the first data row 2022 contains filled field information, a plurality of first keywords expressing the features of the first data row 2022 can be extracted therefrom.

[0087] In step 3024, convert the plurality of first keywords into a first feature vector.

[0088] In this step, common vectorization techniques can be used to convert multiple first keywords into first feature vectors, so that subsequent methods for calculating vector similarity can be used to find candidate data rows that match the first data row 2022. Optionally, the vectorization technique can be the one-hot encoding algorithm, the lexical mapping algorithm (e.g., Word2Vec algorithm), the word embedding algorithm, etc.

[0089] In step 3026, feature matching is performed in the vector database corresponding to the second data table 212 based on the first feature vector to obtain the multiple candidate data rows associated with the first data row 2022.

[0090] In this step, since the first data row 2022 has been converted into a first feature vector, therefore, the method for calculating vector similarity in feature matching can be used to find the feature vectors that match the first data row 2022 (e.g., the similarity is greater than the similarity threshold) from the vector database corresponding to the second data table 212, and then find the second data rows corresponding to these feature vectors as the candidate data rows.

[0091] In this way, multiple candidate data rows associated with the first data row are found through feature matching. It can be understood that, according to different requirements, the similarity threshold can be set. For example, when the similarity threshold is set relatively high, candidate data rows that are more similar to the first data row can be obtained, thus ensuring the recommendation quality; on the contrary, when the similarity threshold is set relatively low, more candidate data rows can be obtained, thus expanding the user's selection range.

[0092] Optionally, the vector database corresponding to the second data table 212 can be a vector database that has been established, that is, a vector database established after each second data row 2122 in the second data table 212 is generated into a second feature vector, and this vector database includes the second feature vectors corresponding to all the second data rows 2122.

[0093] It can be understood that the vector database can be stored on the server side. For example, it is established by the server 106 and stored in the database server 108. Thus, when the terminal device 102A needs to perform feature matching on the feature vectors in the vector database, it can send the first feature vector to the server 106 for it to perform feature matching and then return the matching result to the terminal device 102A. In some scenarios, the terminal device 102A can preload the vector database into local storage, so that feature matching can be facilitated. At this time, the foregoing steps can all be executed locally on the terminal device 102A.

[0094] In some embodiments, if the number of the second data rows 2122 in the second data table 212 is greater than or equal to the second quantity (i.e., the condition for displaying the recommendation control 216 is satisfied) and the vector database corresponding to the second data table 212 has not been established, the vector database can be established based on the multiple second data rows 2122 of the second data table 212. At this time, since the condition for displaying the recommendation control 216 is satisfied and the recommendation control 216 is displayed on the first page 210, in order to ensure the user's recommendation needs, if the vector database has not been established at this time, the vector database can be immediately established, so that the user's recommendation needs can be timely responded to subsequently.

[0095] It can be understood that at this time, the terminal device 102A has obtained the second data table 212. Therefore, the step of establishing the vector database can be performed by the terminal device 102A, and the established vector database can also be stored locally in the terminal device 102A for subsequent feature matching. Of course, the terminal device 102A can also send a request to establish the vector database to the server 106 so that the server 106 establishes the vector database. No matter which method is adopted, it belongs to the protection scope of the present disclosure.

[0096] In some embodiments, as Figure 3C shown, the method for establishing the vector database can further include the following steps.

[0097] In step 312, a plurality of second keywords are extracted from the second data rows.

[0098] In this step, common keyword extraction algorithms can be used to extract the second keywords from the second data rows 2022. Optionally, the keyword extraction algorithm can be the term frequency-inverse document frequency (TF-IDF) algorithm, graph-based ranking algorithms (e.g., TextRank algorithm, PageRank algorithm), and so on. As Figure 2B shown, since the second data rows 2122 contain filled field information, a plurality of second keywords expressing the features of the second data rows 2122 can be extracted therefrom.

[0099] In step 314, the plurality of second keywords are converted into second feature vectors.

[0100] In this step, common vectorization techniques can be used to convert the plurality of second keywords into second feature vectors, so that candidate data rows matching the first data row 2022 can be found by calculating the vector similarity. Optionally, the vectorization technique can be the one-hot encoding algorithm, the lexical mapping algorithm (e.g., Word2Vec algorithm), the word embedding algorithm, and so on.

[0101] In step 316, the vector database is established based on the second feature vector.

[0102] In this step, the vector database can be established by using the already generated second feature vectors, so that the first feature vector can be used to perform feature matching (e.g., vector similarity calculation) with these second feature vectors, and then the second feature vectors with higher similarity can be found, and then the second data row corresponding to the second feature vector with higher similarity is determined as the candidate data row.

[0103] In some embodiments, if the vector database is not established yet (for example, only some of the second data rows in the second data table have generated second feature vectors), then feature matching can be performed between the second feature vectors already generated in the vector database and the first feature vector, so that the recommendation function can be completed based on the already constructed second feature vectors to ensure the execution of the recommendation function.

[0104] In some scenarios, as Figure 1 shown, user 104A and user 104B can collaborate on work, for example, maintaining a table simultaneously. At this time, user 104B can add a second data row to the second data table 212. In some embodiments, in response to the second data table 212 including the newly added second data row, the terminal device 102A and / or the server 106 can update the vector database based on the newly added second data row, so as to ensure the up-to-date state of the data in the vector database. Optionally, when user 104A and / or user 104B modify, delete, etc. the second data row in the second data table 212, the vector database can also be updated based on this, so as to ensure the up-to-date state of the data in the vector database and improve the recommendation accuracy.

[0105] In some embodiments, the data range associated with the first field 204 can be pre-configured. Figure 3D FIG. shows a schematic diagram of a page 320 for configuring a data range according to an embodiment of the present disclosure. As Figure 3D shown, user 104A and / or user 104B can configure the data range associated with the first field 204. Optionally, as Figure 3DAs shown, the data range may include at least one designated data table (e.g., a commodity table), at least one data screening condition of the designated data table (e.g., a business line field includes specific field information), and whether to allow at least one of multiple data rows to be associated in a single field. When the user sets the data range through page 320, the range of the vector database can be narrowed based on the data range, thereby reducing the number of feature matches required and improving matching accuracy. Furthermore, when obtaining candidate data rows, the data range corresponding to the multiple candidate data rows can be determined first, and then based on the data range, the multiple candidate data rows associated with the first data row can be obtained, thereby reducing the number of feature matches required and improving matching accuracy.

[0106] In some embodiments, a machine learning model (e.g., a neural network model) can also be trained based on the vector database created above and the associated first data row or its first feature vector to obtain a recommendation model, and the recommended data row can be subsequently output based on the recommendation model, thereby utilizing the advantages of the machine learning model to implement the recommendation function.

[0107] Continue to refer Figure 3A In step 304, the plurality of candidate data rows are sorted to obtain the sorted plurality of candidate data rows.

[0108] In this step, by sorting multiple candidate data rows, those with higher relevance can be ranked in front for recommendation, thus ensuring the accuracy of the recommendation.

[0109] Optionally, the sorting may be performed based on the degree of vector similarity, so that the candidate data rows that are more matched with the first data row may be placed in front for priority recommendation.

[0110] In step 306, a first number (eg, 5) of the first candidate data rows ranked top among the sorted candidate data rows are determined as the recommended data rows.

[0111] In this way, by displaying the first candidate data row with a higher ranking as a recommended data row in the first page 210, the user can see the second data row that is more relevant to the first data row, thereby making it easier to find the second data row that the user wants to associate with.

[0112] Back to Figure 2E In some embodiments, the first page 210 may also display a replacement control 222, which may be used to replace the recommended data row 220, so that when the user is not satisfied with the current recommended data row, another recommended data row may be replaced. Figure 2EAs shown, the replacement control 222 is located at an associated position (eg, above) of the plurality of recommended data rows 220 , so that the user can more easily observe the control and use it conveniently.

[0113] Further, in response to a trigger instruction for the change control 222 (e.g., clicking the change control 222), the terminal device 102A can re-determine the first number of second candidate data rows ranked higher among the sorted candidate data rows other than the first candidate data rows, and then determine the second candidate data rows as the recommended data rows and replace the first candidate data rows in the first page 210. In other words, the second candidate data rows are used as new recommended data rows to be displayed in the first page 210, thereby replacing the recommended data rows. In this way, since the second candidate data rows ranked higher are selected according to the sorting result, the recommended data rows can also meet the similarity requirement, thereby ensuring the recommendation effect.

[0114] It can be understood that when the user 104A continues to trigger the change control 222, the above steps can be repeatedly executed until all candidate data rows are traversed. At this time, the first candidate data row can be recommended to the user again from the beginning to ensure the execution of the recommendation function.

[0115] As previously mentioned, the process of obtaining multiple candidate data rows associated with the first data row takes time. Therefore, in order to ensure timely response to user needs, in some embodiments, in response to the number of second data rows in the second data table being greater than or equal to the second number (i.e., when the display conditions of the recommendation control are met), the terminal device 102A can preload the multiple candidate data rows associated with the first data row 2022, that is, start executing the method of obtaining candidate data rows when the display conditions of the recommendation control are met, to ensure that the user can respond more quickly and display the recommended data row 220 on the first page 210 when the recommendation control 216 is triggered.

[0116] Continue to refer to Figure 2E , the user 104A can still use the search bar 214 to search for the second data row that he wants to associate, and can search after obtaining the recommended results. Figure 2E The search term is continued to be inputted in the first page 210 shown in the figure to perform the search. After the search term is inputted and the search process is performed, the search results may be displayed in the first page 210, the display of the recommended data row 220 may be stopped, and the display of the recommendation control 216 may be started. Figure 2C or Figure 2D As shown, the display of search results is prioritized and the simplicity of the first page 210 is ensured.

[0117] Continuing to refer to Figure 2C or Figure 2D , in some embodiments, after inputting a search term for searching, user 104A can also continue to use the recommendation function provided by the recommendation control 216. To ensure that the recommendation results match the search intent of user 104A, at this time, in response to a trigger instruction for the recommendation control 216, the terminal device 102A can obtain the multiple recommended data rows based on the search term (e.g., Figure 2C "cap" of Figure 2D "top hat").

[0118] Optionally, the search term can be used as one of the keywords, and a first feature vector can be generated based on the search term and the keywords extracted from the first data row, so that the first feature vector contains the information of the search term. Furthermore, the second feature vector can be matched in combination with the user's search intent to obtain recommended data rows that match the search intent, which may better meet the user's current needs and improve the user experience.

[0119] In some embodiments, as Figure 2E shown, in response to the multiple second data rows 2122 exceeding the display range of the first page 210 along the row direction of the second data rows 2122 (e.g., Figure 2E the horizontal direction), a scroll bar 2126 can be displayed in the first page 210. The scroll bar 2126 is used to move along the row direction (e.g., Figure 2E the horizontal direction) to control the second data rows 2122 and the recommended data rows 220 to slide and display together along the row direction. In this way, by using the scroll bar 2126 to simultaneously control the second data rows 2122 and the recommended data rows 220 to slide and display together along the row direction, it is convenient for the user to view the content of the second data rows 2122 and the recommended data rows 220 in comparison, improving the user experience.

[0120] In some embodiments, as Figure 2E shown, the first field of the recommended data row 220 includes a check box 2202, which can be used by user 104A to select the recommended data row 220, and further association operations can be performed based on this selection. Optionally, when user 104A checks the check box of a certain recommended data row 220, the check box of the corresponding second data row in the second data table 212 is also checked, as Figure 2E shown, so that the user can intuitively see which second data row 2122 in the second data table 212 the recommended data row 220 corresponds to.

[0121] In some embodiments, in response to a selection instruction for at least one target recommended data row (e.g., the first row of recommended data rows) among the multiple recommended data rows 220 (e.g., the first row of recommended data rows is checked and the OK control 250 is clicked), the at least one target recommended data row can be associated with the first field 2024 of the first data row 2022. In this way, the data association operation based on the recommended data row 220 is achieved, enabling the user 104A to view the information of the recommended data row 220 in the first field 2024 of the first data row 2022 in the first data table 202. When the association is a one-way association, the entire row information of the data row can be clicked and viewed in this field of the first data table 202, and further navigation can be made to the second data table 212 associated with this field for viewing. When the association is a two-way association, the data of the second data table 212 can be directly viewed in the first data table 202, and further navigation can be made to the second data table 212. Additionally, it is also possible to jump back to the first data table 202 from the second data table 212 with one click.

[0122] It can be understood that the page of the accompanying drawings combined with the above embodiments is displayed in a landscape orientation. When the terminal devices 102A and 102B are mobile terminals (e.g., mobile phones), the page can be adaptively switched to a portrait orientation for display, which will not be elaborated here.

[0123] As can be seen from the above embodiments, in the table data processing method provided by the embodiments of the present disclosure, when the user uses the association function of the table, the recommended function is used to recommend to the user the recommended data rows that match the first data row, reducing the difficulty for the user to find the data row to be associated. In some cases, the user may be able to find the data row to be associated without searching or filtering, reducing the time for finding the associated data row.

[0124] It should be noted that the method of the embodiments of the present disclosure can be executed by a single device, such as a computer or a server. The method of this embodiment can also be applied to a distributed scenario, where multiple devices cooperate with each other to complete it. In such a distributed scenario, one of the multiple devices can only execute one or more steps of the method of the embodiments of the present disclosure, and these multiple devices will interact with each other to complete the described method.

[0125] It should be noted that some embodiments of the present disclosure have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the above embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0126] Figure 4 FIG. 400 is a schematic flow chart of an exemplary table data processing method 400 provided by an embodiment of the present disclosure. The method 400 can be used to recommend associable data rows. Optionally, the method 400 can be implemented independently by Figure 1 the terminal device 102A or 102B, or can be implemented by interaction among the devices in Figure 1 the system 100.

[0127] As Figure 4 shown, the method 400 may further include the following steps.

[0128] In step 402, in response to a data association request for a first field (e.g., field 2024 of the first row of data in the first data table 202) of a first data row (e.g., the first row of data in the first data table 202) in a first data table (e.g., the first data table 202), a first page (e.g., the first page 210) is displayed. The first page includes a plurality of second data rows (e.g., the second data rows 2122) of a second data table (e.g., the second data table 212) associated with the first field and a recommendation control (e.g., the recommendation control 216). Optionally, the association relationship between the second data table and the first field may be pre-configured in the first data table. Figure 2A in the first data table 202) of the first data row (e.g., the first row of data in the first data table 202), a first page (e.g., the first page 210) is displayed. The first page includes a plurality of second data rows (e.g., the second data rows 2122) of a second data table (e.g., the second data table 212) associated with the first field and a recommendation control (e.g., the recommendation control 216). Optionally, the association relationship between the second data table and the first field may be pre-configured in the first data table. Figure 2A in the first data table 202), a first page (e.g., the first page 210) is displayed. The first page includes a plurality of second data rows (e.g., the second data rows 2122) of a second data table (e.g., the second data table 212) associated with the first field and a recommendation control (e.g., the recommendation control 216). Optionally, the association relationship between the second data table and the first field may be pre-configured in the first data table. Figure 2A of the first row of data in the first data table 202) of the first data row (e.g., the first row of data in the first data table 202), a first page (e.g., the first page 210) is displayed. The first page includes a plurality of second data rows (e.g., the second data rows 2122) of a second data table (e.g., the second data table 212) associated with the first field and a recommendation control (e.g., the recommendation control 216). Optionally, the association relationship between the second data table and the first field may be pre-configured in the first data table. Figure 2A field 2024), a first page (e.g., the first page 210) is displayed. The first page includes a plurality of second data rows (e.g., the second data rows 2122) of a second data table (e.g., the second data table 212) associated with the first field and a recommendation control (e.g., the recommendation control 216). Optionally, the association relationship between the second data table and the first field may be pre-configured in the first data table. Figure 2B the first page 210). The first page includes a plurality of second data rows (e.g., the second data rows 2122) of a second data table (e.g., the second data table 212) associated with the first field and a recommendation control (e.g., the recommendation control 216). Optionally, the association relationship between the second data table and the first field may be pre-configured in the first data table. Figure 2B in the second data table 212) of the second data table (e.g., the second data table 212) associated with the first field and a recommendation control (e.g., the recommendation control 216). Optionally, the association relationship between the second data table and the first field may be pre-configured in the first data table. Figure 2B in the second data table 212), a first page (e.g., the first page 210) is displayed. The first page includes a plurality of second data rows (e.g., the second data rows 2122) of a second data table (e.g., the second data table 212) associated with the first field and a recommendation control (e.g., the recommendation control 216). Optionally, the association relationship between the second data table and the first field may be pre-configured in the first data table. Figure 2B the recommendation control 216). Optionally, the association relationship between the second data table and the first field may be pre-configured in the first data table.

[0129] In step 404, in response to a trigger instruction for the recommendation control, a plurality of recommended data rows (e.g., the recommended data rows 220) corresponding to the first field are displayed on the first page. The plurality of recommended data rows are selected from the second data rows of the second data table (i.e., the recommended data rows also belong to the second data rows in the second data table), and the plurality of recommended data rows are associated with the first data row (i.e., the recommended data rows have a certain association relationship with the first data row). Figure 2E the recommended data rows 220) corresponding to the first field are displayed on the first page. The plurality of recommended data rows are selected from the second data rows of the second data table (i.e., the recommended data rows also belong to the second data rows in the second data table), and the plurality of recommended data rows are associated with the first data row (i.e., the recommended data rows have a certain association relationship with the first data row).

[0130] The table data processing method provided by the embodiment of the present disclosure recommends recommended data rows matching the first data row to the user through the recommendation function when the user uses the association function of the table, thereby reducing the difficulty for the user to find the data rows that he wants to associate. In some cases, the user may be able to find the data rows that he wants to associate without searching or filtering, thereby reducing the time to find the associated data rows.

[0131] In some embodiments, in response to a trigger instruction for the recommendation control, displaying a plurality of recommendation data rows corresponding to the first field on the first page further comprises:

[0132] In response to a trigger instruction for the recommendation control (eg, clicking the recommendation control), information for prompting the user that a recommended data row is being obtained is displayed on the first page (eg, Figure 2F Information 230);

[0133] In response to acquiring the plurality of recommended data rows, displaying the plurality of recommended data rows corresponding to the first field on the first page, referring to Figure 2E shown.

[0134] In this way, in response to a trigger instruction for the recommendation control, information prompting the user that recommended data rows are being obtained can be displayed on the first page first, so that after seeing the information, the user can know that recommended data rows matching the first data row are currently being searched for, and can then wait patiently.

[0135] In some embodiments, before the first page displays a plurality of recommended data rows corresponding to the first field, the method further includes:

[0136] Acquire multiple candidate data rows associated with the first data row;

[0137] Sorting the multiple candidate data rows (for example, sorting them from high to low according to similarity) to obtain the sorted multiple candidate data rows;

[0138] A first number (for example, 3, 4, 5, etc.) of first candidate data rows ranked top among the sorted candidate data rows are determined as the recommended data rows.

[0139] In this way, by displaying the first candidate data row with a higher ranking as a recommended data row on the first page, the user can see the second data row that is more relevant to the first data row, thereby making it easier to find the second data row that the user wants to associate with.

[0140] In some embodiments, the method further comprises:

[0141] On the first page, a replacement control is displayed (e.g., Figure 2E the replacement control 222); wherein, the replacement control is located at an associated position (e.g., above) of the multiple recommended data rows;

[0142] In response to a trigger instruction for the replacement control (e.g., clicking on the replacement control), among the sorted multiple candidate data rows other than the multiple first candidate data rows, the first quantity of multiple second candidate data rows ranked higher are re - determined;

[0143] The multiple second candidate data rows are determined as the multiple recommended data rows and replace the multiple first candidate data rows in the first page.

[0144] In this way, using the multiple second candidate data rows as new recommended data rows to be displayed in the first page realizes the replacement of the recommended data rows. And since the second candidate data rows ranked higher are selected according to the sorting result, the recommended data rows can also meet the similarity requirements, thus ensuring the recommendation effect.

[0145] In some embodiments, the obtaining of the multiple candidate data rows associated with the first data row further includes: determining a data range for screening to obtain the multiple candidate data rows; wherein, the data range includes at least one specified data table (e.g., a commodity table), at least one data screening condition of the specified data table (e.g., the business line field includes specific field information), and at least one of whether to allow associating multiple data rows in a single field; based on the data range, the multiple candidate data rows associated with the first data row are obtained, thereby reducing the number of feature matches required and improving the matching accuracy.

[0146] In some embodiments, the obtaining of the multiple candidate data rows associated with the first data row includes: in response to the number of the second data rows in the second data table being greater than or equal to the second quantity, pre - loading the multiple candidate data rows associated with the first data row, that is, starting to execute the method of obtaining candidate data rows when the display condition of the recommendation control is met, so as to ensure that the user can respond more quickly and the recommended data rows can be displayed on the first page when the recommendation control is triggered.

[0147] In some embodiments, the obtaining of the multiple candidate data rows associated with the first data row further includes:

[0148] Extracting multiple first keywords from the first data row;

[0149] Converting the multiple first keywords into a first feature vector;

[0150] Performing feature matching in the vector database corresponding to the second data table based on the first feature vector to obtain the multiple candidate data rows associated with the first data row.

[0151] In this way, multiple candidate data rows associated with the first data row are found through feature matching. It can be understood that according to different requirements, the similarity threshold can be set. For example, when the similarity threshold is set relatively high, candidate data rows more similar to the first data row can be obtained, thus ensuring the recommendation quality; conversely, when the similarity threshold is set relatively low, more candidate data rows can be obtained, thus expanding the user's selection range.

[0152] In some embodiments, the method further includes: in response to the number of the second data rows in the second data table being greater than or equal to the second quantity and the vector database corresponding to the second data table not being established, establishing the vector database based on the multiple second data rows of the second data table. At this time, since the condition for displaying the recommendation control is met and the recommendation control is displayed on the first page, to ensure the user's recommendation needs, if the vector database has not been established yet, the vector database can be established immediately, so that the user's recommendation needs can be responded to in a timely manner subsequently.

[0153] In some embodiments, establishing the vector database based on the multiple second data rows of the second data table further includes:

[0154] Extracting multiple second keywords from the second data rows;

[0155] Converting the multiple second keywords into second feature vectors;

[0156] Establishing the vector database based on the second feature vectors.

[0157] In this way, the vector database can be established using the already generated second feature vectors, so that the first feature vectors can be used to perform feature matching (e.g., vector similarity calculation) with these second feature vectors, and then the second feature vectors with higher similarity can be found, and further the second data rows corresponding to the second feature vectors with higher similarity are determined as the candidate data rows.

[0158] In some embodiments, performing feature matching in the vector database corresponding to the second data table based on the first feature vector further includes: in response to the vector database not being established yet, performing feature matching between the second feature vectors already generated in the vector database and the first feature vector, so that the recommendation function can be completed according to the already constructed second feature vectors, ensuring the execution of the recommendation function.

[0159] In some embodiments, the method further includes: in response to the second data table including newly added second data rows, updating the vector database based on the newly added second data rows, so as to ensure the up-to-date status of the data in the vector database.

[0160] In some embodiments, the first page further includes a search bar (e.g., Figure 2B search bar 214), the search bar is displayed at the top of the first page, and the display position of the recommendation control includes an associated position of the search bar (e.g., immediately below the search bar); after the first page is displayed, the method further includes: in response to a search term being input in the search bar, searching for the search term in the multiple second data rows of the second data table, and displaying the second data rows that match the search term. In this way, the user can also obtain the second data rows to be associated based on the search function, thus enriching the operation method.

[0161] In some embodiments, the method further includes: in response to a trigger instruction for the recommendation control and a search term being input in the search bar, obtaining the multiple recommended data rows based on the search term, which can make the recommendation result match the search intent, better meet the current needs of the user, and improve the user experience. Optionally, the search term can be used as one of the keywords, and a first feature vector can be generated based on the search term and the keywords extracted from the first data row, so that the first feature vector contains the information of the search term, and then the second feature vector can be matched in combination with the user's search intent to obtain recommended data rows that match the search intent, which may better meet the current needs of the user and improve the user experience.

[0162] In some embodiments, after searching for the search term in the multiple second data rows of the second data table, the method further includes:

[0163] In response to the second data table not including the second data rows that match the search term, displaying information in the first page for prompting the user that there are no current search results (e.g., Figure 2D information 2144);

[0164] Continuing to display the recommendation control on the first page.

[0165] In this way, when user 104A does not find any search results based on the search term, the user can directly use the recommendation function of the recommendation control 216 to obtain the recommended second data rows to shorten the jump link of the recommendation function, without having to return to the initial state to use the recommendation function.

[0166] In some embodiments, the recommended control is located between the search bar and the multiple second data rows; the step of, in response to a trigger instruction for the recommended control, displaying multiple recommended data rows corresponding to the first field on the first page further includes: in response to the trigger instruction for the recommended control, displaying the multiple recommended data rows between the search bar and the multiple second data rows and stopping displaying the recommended control, so as to ensure the priority display of the recommended data rows (located at the upper part of the first page). Since the recommended data rows obtained based on the recommendation function are already displayed, the recommended control can be stopped from being displayed, making the display content of the first page more concise.

[0167] In some embodiments, the step of displaying the first page further includes: in response to the multiple second data rows exceeding the display range of the first page along the row direction of the second data rows, displaying a scroll bar (e.g., Figure 2E scroll bar 2126) on the first page, where the scroll bar is used to move along the row direction to control the second data rows and the recommended data rows to slide and display together along the row direction. In this way, by using the scroll bar to simultaneously control the second data rows and the recommended data rows to slide and display together along the row direction, it is convenient for the user to view the content of the second data rows and the recommended data rows in comparison, improving the user experience.

[0168] In some embodiments, the method further includes: in response to a selection instruction for at least one target recommended data row among the multiple recommended data rows (e.g., checking Figure 2E the first row of the recommended data rows and clicking the confirmation control 250), associating the at least one target recommended data row with the first field of the first data row. In this way, the data association operation based on the recommended data rows is realized, enabling the user to view the information of the recommended data row in the first field of the first data row in the first data table. When the association is a one-way association, the user can click on the field in the first data table to view the entire row information of the data row, and can further jump to the second data table associated with this field for viewing. When the association is a two-way association, the user can directly view the data in the second data table in the first data table, and can further jump to the second data table. Moreover, the user can also jump back to the first data table with one click from the second data table.

[0169] It should be noted that the method of the embodiments of the present disclosure can be executed by a single device, such as a computer or a server. The method of this embodiment can also be applied to a distributed scenario, and multiple devices cooperate with each other to complete it. In this distributed scenario, one of the multiple devices can only execute one or more steps of the method of the embodiments of the present disclosure, and these multiple devices will interact with each other to complete the described method.

[0170] It should be noted that some embodiments of the present disclosure have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the above embodiments and still achieve the desired results. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0171] The embodiments of the present disclosure also provide a computer device for implementing the above method 400. Figure 5 The schematic diagram of the hardware structure of the exemplary computer device 500 provided by the embodiments of the present disclosure is shown. The computer device 500 can be used to implement Figure 1 the server 106, and can also be used to implement Figure 1 the terminal devices 102A and 102B. In some scenarios, the computer device 500 can also be used to implement Figure 1 the database server 108.

[0172] As Figure 5 shown, the computer device 500 may include: a processor 502, a memory 504, a network interface 506, a peripheral interface 508, and a bus 510. Among them, the processor 502, the memory 504, the network interface 506, and the peripheral interface 508 are communicatively connected to each other inside the computer device 500 through the bus 510.

[0173] The processor 502 may be a central processing unit (CPU), an image processor, a neural network processor (NPU), a microcontroller (MCU), a programmable logic device, a digital signal processor (DSP), an application specific integrated circuit (ASIC), or one or more integrated circuits. The processor 502 can be used to execute functions related to the technology described in the present disclosure. In some embodiments, the processor 502 may further include multiple processors integrated as a single logic component. For example, as Figure 5 shown, the processor 502 may include multiple processors 502a, 502b, and 502c.

[0174] The memory 504 can be configured to store data (e.g., instructions, computer code, etc.). As Figure 5As shown, the data stored in the memory 504 may include program instructions (e.g., one or more programs for implementing the method 400 of the embodiments of the present disclosure) and data to be processed (e.g., the memory may store configuration files of other modules, etc.). The processor 502 may also access the program instructions and data stored in the memory 504, and execute the program instructions to operate on the data to be processed. The memory 504 may include a volatile storage device or a non-volatile storage device. In some embodiments, the memory 504 may include a random access memory (RAM), a read-only memory (ROM), an optical disc, a magnetic disk, a hard disk, a solid state drive (SSD), a flash memory, a memory stick, etc.

[0175] The network interface 506 may be configured to provide communication with other external devices to the computer device 500 via a network. The network may be any wired or wireless network capable of transmitting and receiving data. For example, the network may be a wired network, a local wireless network (e.g., Bluetooth, WiFi, near field communication (NFC), etc.), a cellular network, the Internet, or a combination of the above. It can be understood that the type of the network is not limited to the above specific examples.

[0176] The peripheral interface 508 may be configured to connect the computer device 500 to one or more peripheral devices to implement information input and output. For example, the peripheral devices may include input devices such as a keyboard, a mouse, a touchpad, a touch screen, a microphone, various sensors, etc. and output devices such as a display, a speaker, a vibrator, an indicator light, etc.

[0177] The bus 510 may be configured to transmit information between various components of the computer device 500 (e.g., the processor 502, the memory 504, the network interface 506, and the peripheral interface 508), such as an internal bus (e.g., a processor-memory bus), an external bus (USB port, PCI-E bus), etc.

[0178] It should be noted that although the architecture of the above computer device 500 only shows the processor 502, the memory 504, the network interface 506, the peripheral interface 508, and the bus 510, in the specific implementation process, the architecture of the computer device 500 may further include other components necessary for normal operation. In addition, those skilled in the art can understand that the architecture of the above computer device 500 may also only include the components necessary for implementing the solution of the embodiments of the present disclosure, and do not have to include all the components shown in the figure.

[0179] The embodiments of the present disclosure also provide a tabular data processing device. Figure 6 The schematic diagram of an exemplary device 600 provided by the embodiments of the present disclosure is shown. As Figure 6 shown, the device 600 may be used to implement the method 400, and may further include the following modules.

[0180] The first display module 602 is configured to: in response to a data association request for a first field of a first data row in a first data table, display a first page; wherein the first page includes a plurality of second data rows of a second data table associated with the first field and a recommendation control;

[0181] The second display module 604 is configured to: in response to a trigger instruction for the recommendation control, display multiple recommended data rows corresponding to the first field on the first page; wherein the multiple recommended data rows are selected from the second data rows of the second data table, and the multiple recommended data rows are associated with the first data row.

[0182] In some embodiments, the second display module 604 is configured to:

[0183] In response to a trigger instruction for the recommendation control, displaying information on the first page for prompting the user that a recommended data row is being obtained;

[0184] In response to acquiring the multiple recommended data rows, the multiple recommended data rows corresponding to the first field are displayed on the first page.

[0185] In some embodiments, the apparatus further comprises a determining module configured to:

[0186] Acquire multiple candidate data rows associated with the first data row;

[0187] Sorting the multiple candidate data rows to obtain the sorted multiple candidate data rows;

[0188] A first number of first candidate data rows that are ranked top among the sorted candidate data rows are determined as the recommended data rows.

[0189] In some embodiments, the second display module 604 is configured to: display a change control on the first page; wherein the change control is located at an associated position of the plurality of recommended data rows;

[0190] A determination module is configured to: in response to a trigger instruction for the replacement control, redetermine the first number of second candidate data rows that are ranked top among the sorted multiple candidate data rows except the multiple first candidate data rows; determine the multiple second candidate data rows as the multiple recommended data rows and replace the multiple first candidate data rows in the first page.

[0191] In some embodiments, the determination module is configured to:

[0192] Determine a data range for screening to obtain the multiple candidate data rows; wherein, the data range includes at least one specified data table, at least one data screening condition of the specified data table, and at least one of whether to allow associating multiple data rows in a single field;

[0193] Based on the data range, obtain the multiple candidate data rows associated with the first data row.

[0194] In some embodiments, the determination module is configured to:

[0195] In response to the number of the second data rows in the second data table being greater than or equal to the second quantity, preload the multiple candidate data rows associated with the first data row.

[0196] In some embodiments, the determination module is configured to:

[0197] Extract multiple first keywords from the first data row;

[0198] Convert the multiple first keywords into a first feature vector;

[0199] Perform feature matching in the vector database corresponding to the second data table based on the first feature vector to obtain the multiple candidate data rows associated with the first data row.

[0200] In some embodiments, the apparatus further includes an establishment module, configured to:

[0201] In response to the number of the second data rows in the second data table being greater than or equal to the second quantity and the vector database corresponding to the second data table not being established, establish the vector database based on the multiple second data rows of the second data table.

[0202] In some embodiments, the establishment module is configured to:

[0203] Extract multiple second keywords from the second data row;

[0204] Convert the multiple second keywords into a second feature vector;

[0205] Establish the vector database based on the second feature vector.

[0206] In some embodiments, the determination module is configured to:

[0207] In response to the vector database not being established completely, perform feature matching based on the second feature vectors already generated in the vector database and the first feature vector.

[0208] In some embodiments, a building module is configured to:

[0209] In response to the second data table including newly added second data rows, update the vector database based on the newly added second data rows.

[0210] In some embodiments, the first page further includes a search bar, the search bar is displayed at the top of the first page, and the display position of the recommendation control includes an associated position of the search bar; a third display module 606 is configured to: in response to a search term being input in the search bar, search among the multiple second data rows in the second data table based on the search term, and display the second data rows that match the search term.

[0211] In some embodiments, a second display module 604 is configured to: in response to a trigger instruction for the recommendation control and a search term being input in the search bar, obtain the multiple recommended data rows based on the search term.

[0212] In some embodiments, a second display module 604 is configured to:

[0213] In response to the second data table not including the second data rows that match the search term, display, on the first page, information for prompting the user that there are currently no search results;

[0214] Continue to display the recommendation control on the first page.

[0215] In some embodiments, the recommendation control is located between the search bar and the multiple second data rows;

[0216] The second display module 604 is configured to: in response to a trigger instruction for the recommendation control, display the multiple recommended data rows between the search bar and the multiple second data rows and stop displaying the recommendation control.

[0217] In some embodiments, a first display module 602 is configured to: in response to the multiple second data rows exceeding the display range of the first page in the row direction of the second data rows, display a scroll bar on the first page, and the scroll bar is used to move in the row direction to control the second data rows and the recommended data rows to slide and display together in the row direction.

[0218] In some embodiments, the device further includes an association module, configured to:

[0219] In response to a selection instruction for at least one target recommended data row among the multiple recommended data rows, associate the at least one target recommended data row with the first field of the first data row.

[0220] For the convenience of description, when describing the above device, it is divided into various modules according to functions and described separately. Of course, when implementing the present disclosure, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0221] The device of the above embodiment is used to implement the corresponding method 400 in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated herein.

[0222] Based on the same inventive concept, corresponding to the method in any of the above embodiments, the present disclosure further provides a non-volatile computer-readable storage medium including a computer program. When the computer program is executed by one or more processors, the one or more processors are caused to execute the method 400.

[0223] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0224] The computer program stored in the storage medium of the above embodiment is used to cause the one or more processors to execute the method 400 described in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated herein.

[0225] Based on the same inventive concept, corresponding to the method 400 in any of the above embodiments, the present disclosure further provides a computer program product, which includes one or more computer programs. In some embodiments, the one or more computer programs are executable by one or more processors to cause the one or more processors to execute the method 400. Corresponding to the execution subjects of the respective steps in the respective embodiments of the method 400, the processors executing the corresponding steps can belong to the corresponding execution subjects.

[0226] The computer program product of the above embodiment is used to cause a processor to execute the method 400 described in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated herein.

[0227] Those of ordinary skill in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the present disclosure (including the claims) is limited to these examples; under the concept of the present disclosure, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations in different aspects of the embodiments of the present disclosure as described above, and for the sake of brevity, they are not provided in detail.

[0228] In addition, for simplicity of explanation and discussion, and in order not to make the embodiments of the present disclosure difficult to understand, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Further, the devices may be shown in block diagram form in order not to make the embodiments of the present disclosure difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present disclosure are to be implemented (i.e., these details should be fully within the understanding of those skilled in the art). In cases where specific details (such as circuits) are set forth to describe exemplary embodiments of the present disclosure, it will be apparent to those skilled in the art that the embodiments of the present disclosure may be implemented without these specific details or with variations of these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0229] Although the present disclosure has been described in connection with specific embodiments of the present disclosure, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. For example, other memory architectures (such as dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0230] The embodiments of the present disclosure are intended to cover all such alternatives, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present disclosure shall be included within the protection scope of the present disclosure.

Claims

1. A table data processing method, comprising: In response to a data association request for a first field of a first data row in a first data table, displaying a first page; wherein the first page includes a plurality of second data rows of a second data table associated with the first field and a recommendation control; In response to a trigger instruction for the recommendation control, multiple recommended data rows corresponding to the first field are displayed on the first page; wherein the multiple recommended data rows are selected from the second data rows of the second data table, and the multiple recommended data rows are associated with the first data row.

2. The method according to claim 1, wherein, The method of displaying a plurality of recommended data rows corresponding to the first field on the first page in response to a trigger instruction for the recommendation control further comprises: In response to a trigger instruction for the recommendation control, displaying information on the first page for prompting the user that a recommended data row is being obtained; In response to acquiring the multiple recommended data rows, the multiple recommended data rows corresponding to the first field are displayed on the first page.

3. The method according to claim 1, wherein, Before the first page displays a plurality of recommended data rows corresponding to the first field, the method further includes: Acquire multiple candidate data rows associated with the first data row; Sorting the multiple candidate data rows to obtain the sorted multiple candidate data rows; A first number of first candidate data rows that are ranked top among the sorted candidate data rows are determined as the recommended data rows.

4. The method of claim 3, further comprising: Displaying a change control on the first page; wherein the change control is located at an associated position of the plurality of recommended data rows; In response to a trigger instruction for the replacement control, re-determine the first number of second candidate data rows ranked top among the sorted candidate data rows except the first candidate data rows; The plurality of second candidate data rows are determined as the plurality of recommended data rows and replace the plurality of first candidate data rows in the first page.

5. The method according to claim 3, wherein, The acquiring of a plurality of candidate data rows associated with the first data row further comprises: Determine a data range for filtering to obtain the plurality of candidate data rows; wherein the data range includes at least one of at least one designated data table, at least one data filtering condition of the designated data table, and whether to allow associating multiple data rows in a single field; Based on the data range, the plurality of candidate data rows associated with the first data row are obtained.

6. The method according to claim 3, wherein, The acquiring a plurality of candidate data rows associated with the first data row comprises: In response to the number of the second data rows in the second data table being greater than or equal to a second number, the plurality of candidate data rows associated with the first data row are preloaded.

7. The method according to claim 3, wherein, The acquiring of a plurality of candidate data rows associated with the first data row further comprises: Extracting a plurality of first keywords from the first data row; Converting the plurality of first keywords into a first feature vector; Performing feature matching in the vector database corresponding to the second data table based on the first feature vector to obtain the multiple candidate data rows associated with the first data row.

8. The method according to claim 7, further comprising: In response to the number of the second data rows in the second data table being greater than or equal to a second quantity and the vector database corresponding to the second data table not being established, establishing the vector database based on the multiple second data rows of the second data table.

9. The method according to claim 8, wherein, The establishing the vector database based on the multiple second data rows of the second data table further comprises: Extracting a plurality of second keywords from the second data rows; Converting the plurality of second keywords into second feature vectors; Establishing the vector database based on the second feature vectors.

10. The method according to claim 9, wherein, The performing feature matching in the vector database corresponding to the second data table based on the first feature vector further comprises: In response to the vector database not being established yet, performing feature matching between the second feature vectors already generated in the vector database and the first feature vector.

11. The method according to claim 8, further comprising: In response to the second data table including newly added second data rows, updating the vector database based on the newly added second data rows.

12. The method according to claim 1, wherein, The first page further includes a search bar, the search bar is displayed at the top of the first page, and the display position of the recommendation control includes an associated position of the search bar; After displaying the first page, the method further comprises: In response to a search term being input in the search bar, searching in the multiple second data rows of the second data table based on the search term, and displaying the second data rows that match the search term.

13. The method according to claim 12, further comprising: In response to a trigger instruction for the recommendation control and the search term being input in the search bar, obtaining the multiple recommended data rows based on the search term.

14. The method according to claim 12, wherein, After searching in the multiple second data rows of the second data table based on the search term, the method further comprises: In response to the second data table not including the second data rows that match the search term, displaying in the first page information for prompting the user that there are no current search results; Continuing to display the recommendation control on the first page.

15. The method according to claim 12, wherein The recommendation control is located between the search bar and the multiple second data rows; The displaying, in response to a trigger instruction for the recommendation control, the multiple recommended data rows corresponding to the first field on the first page further comprises: In response to a trigger instruction for the recommendation control, displaying the multiple recommended data rows between the search bar and the multiple second data rows and stopping displaying the recommendation control.

16. The method according to claim 15, wherein, The displaying the first page further comprises: In response to the multiple second data rows exceeding the display range of the first page along the row direction of the second data rows, displaying a scroll bar on the first page, the scroll bar being used to move along the row direction to control the sliding display of the second data rows and the recommended data rows along the row direction.

17. The method according to any one of claims 1 to 16, further comprising: In response to a selection instruction for at least one target recommended data row among the plurality of recommended data rows, associating the at least one target recommended data row with the first field of the first data row.

18. A table data processing device, comprising: A first display module configured to: in response to a data association request for a first field of a first data row in a first data table, display a first page; wherein the first page includes a plurality of second data rows of a second data table associated with the first field and a recommendation control; A second display module configured to: in response to a trigger instruction for the recommendation control, display a plurality of recommended data rows corresponding to the first field on the first page; wherein the plurality of recommended data rows are selected from the second data rows of the second data table, and the plurality of recommended data rows are associated with the first data row.

19. A computer device, comprising one or more processors, a memory; and one or more programs, wherein the one or more programs are stored in the memory and executed by the one or more processors, and the one or more programs include instructions for performing the method according to any one of claims 1 to 17.

20. A non-volatile computer-readable storage medium containing a computer program, which, when executed by one or more processors, causes the one or more processors to perform the method according to any one of claims 1 to 17.

21. A computer program product, comprising one or more computer programs, which, when executed by one or more processors, implement the method according to any one of claims 1 to 17.

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