Abstract display method and device of data board, medium, equipment and program product

Abstract

The invention discloses an abstract display method and device for a data board, a medium, equipment and a program product, and the method comprises the steps: responding to a triggering operation for an abstract of the data board, and splitting a display chart according to the content type of the display chart in the data board, so as to obtain at least one chart group; generating an abstract of each chart group through a large model; based on the abstract corresponding to each chart group, a target prompt word is constructed, a target abstract for the data board is generated through the large model based on the target prompt word, and the target prompt word is used for indicating the large model to summarize the abstract corresponding to each chart group. Generating an abstract for the data board; and displaying the target abstract of the data board. The readability and the understandability of the data board can be improved, the efficiency and the accuracy of information acquisition are improved, the data analysis process is optimized, and a user can make a business decision conveniently.

Description

Technical Field

[0001] The present disclosure relates to the fields of large language models, large models, intelligent agents and artificial intelligence technology, and in particular, to a summary display method, device, medium, equipment and program product for a data dashboard. Background Art

[0002] With the continuous expansion of actual business, the demand for multi-dimensional analysis of business data is growing. Although different data dashboards and charts can be used to display and analyze data in multiple dimensions, as the number of data dashboards and charts increases, the complexity of data information also increases, and the readability and comprehensibility of data dashboards decrease, which leads to low efficiency in information acquisition. Summary of the invention

[0003] This summary is provided to introduce concepts in a brief form that will be described in detail in the detailed description below. This summary is not intended to identify key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0004] In a first aspect, the present disclosure provides a summary display method of a data dashboard, comprising: In response to a triggering operation on a data dashboard summary, the displayed chart is split according to a content type of a displayed chart in the data dashboard to obtain at least one chart group; generating a summary of each of said chart groups by means of a large model; Based on the summary corresponding to each of the chart groups, a target prompt word is constructed, and a target summary for the data dashboard is generated based on the target prompt word through the large model, wherein the target prompt word is used to instruct the large model to summarize the summary corresponding to each of the chart groups and generate a summary for the data dashboard; The target summary of the data dashboard is displayed.

[0005] In a second aspect, the present disclosure provides a summary display device for a data dashboard, comprising: A splitting module, configured to respond to a triggering operation on a data dashboard summary and split the displayed chart according to the content type of the displayed chart in the data dashboard to obtain at least one chart group; A first generating module, configured to generate a summary of each of the chart groups by using a large model; A second generating module is used to construct a target prompt word based on the summary corresponding to each of the chart groups, and generate a target summary for the data dashboard based on the target prompt word through the large model, wherein the target prompt word is used to instruct the large model to summarize the summary corresponding to each of the chart groups and generate a summary for the data dashboard; A display module is used to display the target summary of the data dashboard.

[0006] In a third aspect, the present disclosure provides a computer-readable medium having a computer program stored thereon, which implements the steps of the method described in the first aspect when the program is executed by a processing device.

[0007] In a fourth aspect, the present disclosure provides an electronic device, including: a storage device having a computer program stored thereon; A processing device is used to execute the computer program in the storage device to implement the steps of the method in the first aspect.

[0008] In a fifth aspect, the present disclosure provides a computer program product, comprising a computer program, which implements the steps of the method described in the first aspect when executed by a processor.

[0009] Through the above technical solution, the displayed chart can be split according to the content type of the displayed chart in the data dashboard to obtain at least one chart group, and the target prompt word can be constructed based on the summary of each chart group generated by the large model. Finally, the target summary for the data dashboard is generated based on the target prompt word through the large model, and the target summary of the data dashboard is displayed. By adopting the above method, it is possible to generate chart group summaries of different content types based on the large model grouping, and summarize and generate summaries for the data dashboard, thereby improving the readability and comprehensibility of the data dashboard, improving the efficiency and accuracy of information acquisition, optimizing the data analysis process, and facilitating users to make business decisions.

[0010] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale. In the drawings: Figure 1 is a display schematic diagram of a data dashboard according to an exemplary embodiment of the present disclosure; Figure 2It is a flowchart of a summary display method of a data dashboard according to an exemplary embodiment of the present disclosure; Figure 3 is a schematic diagram showing a summary of a data dashboard according to an exemplary embodiment of the present disclosure; Figure 4 is a process schematic diagram of a summary display method of a data dashboard according to an exemplary embodiment of the present disclosure; Figure 5 is a structural block diagram of a summary display device of a data dashboard according to an exemplary embodiment of the present disclosure; Figure 6 It is a schematic structural diagram of an electronic device according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0012] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0013] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0014] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0015] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0016] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0017] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0018] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0019] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed 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, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0020] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. 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.

[0021] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0022] At the same time, it is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and relevant provisions.

[0023] like Figure 1 As shown, the data dashboard can display charts of different chart types according to the configuration, and different charts usually involve multiple data dimensions. The complex data information reduces the readability and comprehensibility of the data dashboard, which in turn leads to low efficiency in information acquisition.

[0024] In view of this, the present disclosure provides a summary display method, device, medium, equipment and program product for a data dashboard to solve the above technical problems.

[0025] The embodiments of the present disclosure are further explained below with reference to the accompanying drawings.

[0026] Figure 2 is a flowchart of a summary display method of a data dashboard according to an exemplary embodiment of the present disclosure, referring to Figure 2 , the method comprising: S201: In response to a triggering operation on a data dashboard summary, split the displayed chart in the data dashboard according to the content type of the chart, to obtain at least one chart group.

[0027] S202: Generate a summary of each chart grouping through the large model.

[0028] For example, the large model can be one or more, and multiple large models can generate summaries for each chart group in parallel to improve the efficiency of summaries of chart groups. The large model can be a large language model, which can first identify the displayed chart to obtain description information and then input it into the large language model to generate the corresponding summary, or it can be a multimodal large model, which can directly input the chart into the multimodal large model to generate the corresponding summary. The specific setting can be based on demand, and the present disclosure does not limit this.

[0029] S203: Based on the summary corresponding to each chart group, a target prompt word is constructed, and a target summary for the data dashboard is generated based on the target prompt word through the big model, wherein the target prompt word is used to instruct the big model to summarize the summary corresponding to each chart group and generate a summary for the data dashboard.

[0030] For example, in an embodiment of the present disclosure, the big model may include a first sub-model and a second sub-model, wherein the first sub-model is used to generate a summary of a chart grouping, and the second sub-model is used to generate a summary of a data dashboard, or the summary of the chart grouping and the summary of the data dashboard are generated by the same big model, which may be other machine learning models in addition to a big language model, and may be set specifically according to requirements, and the present disclosure does not impose any restrictions on this.

[0031] S204: Display the target summary of the data dashboard.

[0032] By adopting the above method, it is possible to generate chart group summaries of different content types based on the large model grouping, and summarize and generate summaries for the data dashboard, thereby improving the readability and comprehensibility of the data dashboard, improving the efficiency and accuracy of information acquisition, optimizing the data analysis process, and facilitating users to make business decisions.

[0033] In a possible manner, in response to a triggering operation on a data dashboard summary, the displayed chart is split according to the content type of the chart displayed in the data dashboard to obtain at least one chart group, including: while displaying the data dashboard, displaying an intelligent interactive control for generating a data dashboard summary, and in response to a triggering operation on the intelligent interactive control, splitting the displayed chart according to the content type of the chart displayed in the data dashboard to obtain at least one chart group; or, displaying an intelligent dialogue interface, and in response to the content for displaying the data dashboard summary input by the user in natural language in the intelligent dialogue interface, splitting the displayed chart according to the content type of the chart displayed in the data dashboard to obtain at least one chart group; or, in response to a pre-set scheduled task for displaying the data dashboard summary, splitting the displayed chart according to the content type of the chart displayed in the data dashboard to obtain at least one chart group.

[0034] For example, Figure 3 As shown, while displaying the data dashboard, the intelligent interactive control for generating the data dashboard summary can be displayed, and the generation process of the data dashboard summary is triggered in response to the triggering operation of the intelligent interactive control, and the data dashboard summary is displayed as shown in FIG. Figure 3 The data dashboard summary shown may be displayed in a floating layer, a pop-up box, or other forms, and the present disclosure does not limit this.

[0035] For example, Figure 3 As shown, the intelligent dialogue interface is associated with an intelligent object connected to the large model. The user can input content for displaying the data dashboard summary in natural language in the intelligent dialogue interface, thereby triggering the generation process of the data dashboard summary and displaying the data dashboard summary on the intelligent dialogue interface, thereby realizing the summary generation of the data dashboard in the form of dialogue.

[0036] For example, a scheduled task for displaying a data dashboard summary can be pre-set to periodically trigger the generation process of the data dashboard summary, such as generating a daily summary every day, generating a monthly summary every month, and so on. The generated summary can be displayed in a preset position of the data dashboard in the form of a floating layer or pop-up box when the user queries the data dashboard, or it can be displayed in response to the user's trigger operation on the dashboard summary. The specific setting can be based on demand, and the present disclosure is not limited to this.

[0037] It is worth noting that if Figure 4As shown, the displayed charts can be grouped according to the configuration logic of the data dashboard. For example, the data dashboard is configured with chart data for business A and chart data for business B. It can also be understood that the displayed charts of the data dashboard are grouped according to different content types. The specific settings can be made according to the needs, and the present disclosure does not limit this. Since the data dimensions and key information of charts of different content types are different, by first generating corresponding summaries for different content types and then generating the dashboard summary, the accuracy of the dashboard summary can be improved, which is convenient for users to make business decisions.

[0038] It should be understood that if Figure 4 As shown, the overview table that brings together multiple charts can be treated as a single group to enable the large model to perform an overview analysis of the entire data dashboard, and then other charts can be grouped according to different content types to generate summaries, so that different charts can be analyzed in detail, thereby enabling an overall analysis of the data dashboard from the overall to the details, thereby improving the accuracy of the dashboard summary and facilitating users to make business decisions.

[0039] In a possible manner, a summary of each chart grouping is generated through a large model, including: for each chart grouping, splitting the chart grouping according to the chart type of each chart in the chart grouping to obtain at least one target chart, wherein one target chart corresponds to one chart type; generating a summary of each target chart through the large model; for each chart grouping, generating a summary of the chart grouping through the large model according to the summary of each target chart in the chart grouping.

[0040] For example, Figure 4 As shown, each chart group can also be split according to different chart types, such as trend charts, data tables, pie charts, etc. Since different chart types have different data analysis methods, by first generating corresponding summaries for charts of different chart types, and then summarizing and generating summaries of chart groups, the accuracy of the final dashboard summary can be improved, which is convenient for users to make business decisions.

[0041] In a possible manner, a summary of each target chart is generated through a large model, including: for each target chart, according to the chart type of the target chart, determining a prompt word template corresponding to the target chart from preset prompt word templates, constructing a first prompt word according to the target chart and the prompt word template corresponding to the target chart, and generating a summary of the target chart based on the first prompt word through the large model; wherein the first prompt word is used to instruct the large model to interpret the target chart and generate a summary of the target chart.

[0042] For example, different prompt word templates can be set in advance for different chart types. Figure 4, based on the chart type, select the corresponding prompt word template from the preset prompt word template to build the prompt word, such as "perform data trend analysis + trend chart on the following table", and then input the prompt word into the big model to get the summary for the chart. In this way, corresponding summaries can be generated for charts of different chart types, improving the accuracy of the final dashboard summary and facilitating users to make business decisions.

[0043] In a possible manner, according to the chart type of the target chart, a prompt word template corresponding to the target chart is determined from preset prompt word templates, including: when the target chart is a chart used to characterize data trends, determining it from the preset prompt word templates; when the target chart is a chart including multiple data values, determining the prompt word template for filtering key data values ​​from the preset prompt word templates as the prompt word template corresponding to the target chart.

[0044] For example, when the target chart is a trend chart, a prompt word template for describing data trends can be selected as the prompt word template corresponding to the target chart. When the target chart is a chart including multiple data values, a prompt word template for filtering key data values ​​can be selected as the prompt word template corresponding to the target chart, such as analyzing the year-on-year comparison, maximum value, minimum value, etc. between multiple data values. When the target chart is a pie chart, a prompt word template for analyzing data proportion can be selected as the prompt word template corresponding to the target chart, etc., which can be specifically configured according to actual business scenarios, and the present disclosure does not limit this.

[0045] In a possible manner, a summary of the chart grouping is generated by a large model according to the summary of each target chart in the chart grouping, including: constructing a second prompt word based on the summary of each target chart in the chart grouping, wherein the second prompt word is used to instruct the large model to summarize the summary of each target chart in the chart grouping and generate a summary for the chart grouping; generating a summary of the chart grouping based on the second prompt word by the large model.

[0046] For example, continue to refer to Figure 4 , taking chart group 1 as an example, after obtaining abstract 1.1 and abstract 1.2, a merge prompt word 1 is constructed based on abstract 1.1 and abstract 1.2, such as "merge abstract 1.1 and abstract 1.2", and the merge prompt word 1 is input into the big model, and the big model is used to summarize and generate the abstract of chart group 1. Among them, the big model can not only merge multiple abstracts, but also reorganize the text description of the summarized abstract to improve the readability and comprehensibility of the abstract.

[0047] Similarly, continue to refer to Figure 4 , for the summaries of multiple chart groups, corresponding merge prompt words 2 can also be constructed, and then the summaries of multiple chart groups are merged through the large model, and the text description of the summarized summaries is reorganized to obtain the final kanban summary.

[0048] By adopting the above method, the dashboard content is split, and then the data of the split charts are analyzed and summarized through the big model, and the summary is summarized through the big model to automatically obtain the final overall dashboard summary. The summary can assist users to view and understand more data, for example, it can automatically analyze the long-term fluctuation trend of data, etc., to improve the efficiency of viewing the data dashboard.

[0049] Based on the same concept, the present disclosure provides a summary display device for a data dashboard, such as Figure 5 As shown, the summary display device 500 of the data dashboard includes: A splitting module 501 is used for responding to a triggering operation on a data dashboard summary and splitting the displayed chart according to the content type of the displayed chart in the data dashboard to obtain at least one chart group; A first generating module 502, for generating a summary of each of the chart groups by using a large model; The second generating module 503 is used to construct a target prompt word based on the summary corresponding to each of the chart groups, and generate a target summary for the data dashboard based on the target prompt word through the large model, wherein the target prompt word is used to instruct the large model to summarize the summary corresponding to each of the chart groups and generate a summary for the data dashboard; The display module 504 is used to display the target summary of the data dashboard.

[0050] Optionally, the first generating module 502 is used to: For each of the chart groups, the chart group is split according to the chart type of each chart in the chart group to obtain at least one target chart, wherein one target chart corresponds to one chart type; generating a summary of each of the target graphs by using the large model; For each of the chart groups, a summary of the chart group is generated by the large model according to the summary of each target chart in the chart group.

[0051] Optionally, the first generating module 502 is used to: For each of the target charts, according to the chart type of the target chart, a prompt word template corresponding to the target chart is determined from preset prompt word templates, a first prompt word is constructed according to the target chart and the prompt word template corresponding to the target chart, and a summary of the target chart is generated based on the first prompt word by the large model; The first prompt word is used to instruct the large model to interpret the target chart and generate a summary of the target chart.

[0052] Optionally, the first generating module 502 is used to: When the target chart is a chart for representing data trends, determining a prompt word template for describing data trends from preset prompt word templates as the prompt word template corresponding to the target chart; When the target chart is a chart including multiple data values, a prompt word template for screening key data values ​​is determined from preset prompt word templates as the prompt word template corresponding to the target chart.

[0053] Optionally, the first generating module 502 is used to: Based on the summary of each target chart in the chart group, construct a second prompt word, wherein the second prompt word is used to instruct the large model to summarize the summary of each target chart in the chart group and generate a summary for the chart group; A summary of the chart grouping is generated based on the second prompt word by the large model.

[0054] Optionally, the splitting module 501 is used to: While displaying the data dashboard, display an intelligent interactive control for generating a summary of the data dashboard, and in response to a triggering operation on the intelligent interactive control, split the displayed chart according to the content type of the chart displayed in the data dashboard to obtain at least one chart group; or Displaying an intelligent dialogue interface, and in response to the content for displaying the data dashboard summary input by the user in the intelligent dialogue interface in a natural language, splitting the displayed chart according to the content type of the chart displayed in the data dashboard to obtain at least one chart group; or In response to a preset timed task for displaying the data dashboard summary, the displayed chart is split according to the content type of the chart displayed in the data dashboard to obtain at least one chart group.

[0055] Based on the same concept, an embodiment of the present disclosure further provides a computer-readable medium on which a computer program is stored. When the program is executed by a processing device, the steps of the summary display method of the above-mentioned data dashboard are implemented.

[0056] Based on the same concept, the present disclosure also provides an electronic device, which may include: a storage device having a computer program stored thereon; A processing device is used to execute the computer program in the storage device to implement the steps of the summary display method of the data dashboard.

[0057] Based on the same concept, an embodiment of the present disclosure further provides a computer program product, including a computer program, which implements the steps of the summary display method of the above data dashboard when executed by a processor.

[0058] Reference below Figure 6 , which shows a schematic diagram of the structure of an electronic device 600 suitable for implementing the embodiment of the present disclosure. The terminal device in the embodiment of the present disclosure may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0059] like Figure 6 As shown, the electronic device 600 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic device 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0060] Typically, the following devices may be connected to the I / O interface 605: an input device 606 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 608 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 609. The communication device 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6 The electronic device 600 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0061] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device 609, or installed from a storage device 608, or installed from a ROM 602. When the computer program is executed by the processing device 601, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0062] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. Computer readable signal media may also be any computer readable medium other than computer readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0063] In some embodiments, any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol) can be used for communication, and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0064] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0065] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: responds to a trigger operation on a data dashboard summary, splits the displayed chart according to the content type of the displayed chart in the data dashboard to obtain at least one chart group; generates a summary of each of the chart groups through a large model; constructs a target prompt word based on the summary corresponding to each of the chart groups, and generates a target summary for the data dashboard based on the target prompt word through the large model, wherein the target prompt word is used to instruct the large model to summarize the summary corresponding to each of the chart groups and generate a summary for the data dashboard; and displays the target summary of the data dashboard.

[0066] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including, but not limited to, object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0067] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0068] The modules involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a module does not, in some cases, limit the module itself.

[0069] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0070] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0071] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0072] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0073] Although the subject matter has been described in language specific to structural features and / or method logic actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims. Regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

Claims

1. A summary display method for a data dashboard, characterized in that: include: In response to a triggering operation on a data dashboard summary, the displayed chart is split according to a content type of a displayed chart in the data dashboard to obtain at least one chart group; generating a summary of each of said chart groups by means of a large model; Based on the summary corresponding to each of the chart groups, a target prompt word is constructed, and a target summary for the data dashboard is generated based on the target prompt word through the large model, wherein the target prompt word is used to instruct the large model to summarize the summary corresponding to each of the chart groups and generate a summary for the data dashboard; The target summary of the data dashboard is displayed.

2. The summary display method of the data dashboard according to claim 1, characterized in that: The step of generating a summary of each of the chart groups by using a large model includes: For each of the chart groups, the chart group is split according to the chart type of each chart in the chart group to obtain at least one target chart, wherein one target chart corresponds to one chart type; generating a summary of each of the target graphs by means of the large model; For each of the chart groups, a summary of the chart group is generated by the large model according to the summary of each target chart in the chart group.

3. The summary display method of the data dashboard according to claim 2, characterized in that: The summary of each target chart is generated by the large model, including: For each of the target charts, according to the chart type of the target chart, a prompt word template corresponding to the target chart is determined from preset prompt word templates, a first prompt word is constructed according to the target chart and the prompt word template corresponding to the target chart, and a summary of the target chart is generated based on the first prompt word by the large model; The first prompt word is used to instruct the large model to interpret the target chart and generate a summary of the target chart.

4. The summary display method of the data dashboard according to claim 3, characterized in that: The step of determining the prompt word template corresponding to the target chart from preset prompt word templates according to the chart type of the target chart includes: When the target chart is a chart for representing data trends, determining a prompt word template for describing data trends from preset prompt word templates as the prompt word template corresponding to the target chart; When the target chart is a chart including multiple data values, a prompt word template for screening key data values ​​is determined from preset prompt word templates as the prompt word template corresponding to the target chart.

5. The summary display method of the data dashboard according to claim 2, characterized in that: The step of generating a summary of the chart group according to the summary of each target chart in the chart group by using the large model includes: Based on the summary of each target chart in the chart group, construct a second prompt word, wherein the second prompt word is used to instruct the large model to summarize the summary of each target chart in the chart group and generate a summary for the chart group; A summary of the chart grouping is generated based on the second prompt word by the large model.

6. The summary display method of a data dashboard according to any one of claims 1 to 5, characterized in that: In response to the triggering operation on the data dashboard summary, the displayed chart is split according to the content type of the displayed chart in the data dashboard to obtain at least one chart group, including: While displaying the data dashboard, display an intelligent interactive control for generating a summary of the data dashboard, and in response to a triggering operation on the intelligent interactive control, split the displayed chart according to the content type of the chart displayed in the data dashboard to obtain at least one chart group; or Displaying an intelligent dialogue interface, and in response to the content for displaying the data dashboard summary input by the user in the intelligent dialogue interface in a natural language, splitting the displayed chart according to the content type of the chart displayed in the data dashboard to obtain at least one chart group; or In response to a preset timed task for displaying the data dashboard summary, the displayed chart is split according to the content type of the chart displayed in the data dashboard to obtain at least one chart group.

7. A summary display device for a data dashboard, characterized in that: include: A splitting module, configured to respond to a triggering operation on a data dashboard summary and split the displayed chart according to the content type of the displayed chart in the data dashboard to obtain at least one chart group; A first generating module, configured to generate a summary of each of the chart groups by using a large model; A second generating module is used to construct a target prompt word based on the summary corresponding to each of the chart groups, and generate a target summary for the data dashboard based on the target prompt word through the large model, wherein the target prompt word is used to instruct the large model to summarize the summary corresponding to each of the chart groups and generate a summary for the data dashboard; A display module is used to display the target summary of the data dashboard.

8. A computer readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processing device, the steps of the method according to any one of claims 1 to 6 are implemented.

9. An electronic device, characterized in that: include: a storage device having a computer program stored thereon; A processing device, configured to execute the computer program in the storage device to implement the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images