Data analysis method and device, readable medium and electronic equipment

Abstract

The invention relates to a data analysis method and device, a readable medium and electronic equipment, and the method comprises the steps: responding to a data analysis instruction input by a user, sending the data analysis instruction to a server, triggering the server to obtain interaction feedback data, analyzing the interaction feedback data through a data analysis model, and obtaining an analysis result, the analysis result is pushed to the terminal device, and the interaction feedback data comprises feedback information of an interaction function in the application program; and displaying an analysis result. According to the technical scheme, after a user inputs the data analysis instruction, the data analysis instruction can be sent to the server to trigger the server to obtain the interaction feedback data, the interaction feedback data are analyzed through the data analysis model, and the analysis result of the interaction feedback data is obtained. Therefore, the interaction feedback data can be automatically analyzed through the data analysis model, and the analysis efficiency of the interaction feedback data and the accuracy of the analysis result are improved.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular, to a data analysis method, apparatus, readable medium, and electronic device. Background Art

[0002] To improve the service quality of products, after an application is launched, feedback information of users is generally collected and analyzed to optimize the functions of the application according to the feedback information of users.

[0003] In related technologies, the feedback information of users is generally analyzed manually, which has problems of low analysis efficiency and inaccurate analysis results. Summary of the Invention

[0004] This Summary of the Invention section is provided to introduce concepts in a brief form, which will be described in detail in the following Detailed Description section. This Summary of the Invention section is not intended to identify key features or essential features of the claimed technical solution, nor is it intended to be used to limit the scope of the claimed technical solution.

[0005] In a first aspect, the present disclosure provides a data analysis method applied to a terminal device. The method includes:

[0006] In response to a data analysis instruction input by a user, sending the data analysis instruction to a server to trigger the server to obtain interaction feedback data, and analyzing the interaction feedback data through a data analysis model to obtain an analysis result, and pushing the analysis result to the terminal device, where the interaction feedback data includes feedback information on an interaction function in an application;

[0007] Displaying the analysis result.

[0008] In a second aspect, the present disclosure provides a data analysis method applied to a server. The method includes:

[0009] After receiving a data analysis instruction sent by a terminal device, obtaining interaction feedback data, where the data analysis instruction is input by a user in the terminal device, and the interaction feedback data includes feedback information on an interaction function in an application;

[0010] Analyzing the interaction feedback data through a data analysis model to obtain an analysis result;

[0011] Pushing the analysis result to the terminal device so that the terminal device displays the analysis result.

[0012] In a third aspect, the present disclosure provides a data analysis apparatus. The apparatus includes:

[0013] A first sending module, configured to send the data analysis instruction to a server in response to a data analysis instruction input by a user, so as to trigger the server to obtain interaction feedback data, analyze the interaction feedback data through a data analysis model to obtain an analysis result, and push the analysis result to the terminal device, where the interaction feedback data includes feedback information on an interaction function in an application program;

[0014] A first display module, configured to display the analysis result.

[0015] In a fourth aspect, the present disclosure provides a data analysis device, where the device includes:

[0016] An acquisition module, configured to acquire interaction feedback data after receiving a data analysis instruction sent by a terminal device, where the data analysis instruction is input by a user in the terminal device, and the interaction feedback data includes feedback information on an interaction function in an application program;

[0017] An analysis module, configured to analyze the interaction feedback data through a data analysis model to obtain an analysis result;

[0018] A push module, configured to push the analysis result to a terminal device so that the terminal device displays the analysis result.

[0019] In a fifth aspect, the present disclosure provides a computer-readable medium, on which a computer program is stored, and when the program is executed by a processing device, the steps of the method according to any one of the first aspect or the second aspect are implemented.

[0020] In a sixth aspect, the present disclosure provides an electronic device, including:

[0021] A storage device, on which a computer program is stored;

[0022] 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 the first aspect or the second aspect.

[0023] Through the above technical solutions, after a user inputs a data analysis instruction, the data analysis instruction can be sent to a server to trigger the server to obtain interaction feedback data, and the interaction feedback data is analyzed through a data analysis model to obtain an analysis result of the interaction feedback data. Thus, the interaction feedback data can be automatically analyzed through the data analysis model. Compared with the related art in which the feedback information of a user is analyzed in a manual manner, the way of analyzing the interaction feedback data in the present disclosure can improve the analysis efficiency of the interaction feedback data and the accuracy of the analysis result.

[0024] Other features and advantages of the present disclosure will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In conjunction with the accompanying drawings and with reference to the following detailed description, the above and other features, advantages, and aspects of the embodiments of the present disclosure will become more apparent. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic and that the elements and components are not necessarily drawn to scale. In the drawings:

[0026] Figure 1 is a flowchart of a data analysis shown according to an exemplary embodiment of the present disclosure;

[0027] Figure 2 is a schematic diagram showing an analysis result shown according to an exemplary embodiment of the present disclosure;

[0028] Figure 3 is a schematic diagram showing another analysis result shown according to an exemplary embodiment of the present disclosure;

[0029] Figure 4 is a schematic diagram showing another analysis result shown according to an exemplary embodiment of the present disclosure;

[0030] Figure 5 is a schematic diagram showing another analysis result shown according to an exemplary embodiment of the present disclosure;

[0031] Figure 6 is a flowchart of another data analysis shown according to an exemplary embodiment of the present disclosure;

[0032] Figure 7 is a block diagram of the structure of a data analysis device shown according to an exemplary embodiment of the present disclosure;

[0033] Figure 8 is a block diagram of the structure of another data analysis device shown according to an exemplary embodiment of the present disclosure;

[0034] Figure 9 is a schematic diagram of the structure of an electronic device shown according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0035] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Instead, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of protection of the present disclosure.

[0036] It should be understood that the various steps described in the method embodiments of the present disclosure can be executed 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 regard.

[0037] As used herein, the term "including" and its variations are open-ended, that is, "including but not limited to". The term "based on" means "at least partially based 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.

[0038] It should be noted that the concepts such as "first", "second", etc. mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependent relationships.

[0039] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly stated in the context, it should be understood as "one or more".

[0040] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only for illustrative purposes and are not used to limit the scope of these messages or information.

[0041] It can be understood that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, usage scopes, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to users and the authorization of users should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0042] For example, when responding 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 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.

[0043] As an optional but non-limiting implementation manner, the manner of sending a prompt message to the user in response to receiving an active request from the user 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.

[0044] It should be understood that the above notification and the process of obtaining user authorization are only illustrative and do not limit the implementation manner of the present disclosure. Other manners that comply with relevant laws and regulations can also be applied to the implementation manner of the present disclosure.

[0045] Meanwhile, it should be understood that the data involved in the present technical solution (including but not limited to the data itself, the acquisition or use of the data) should comply with the requirements of corresponding laws, regulations and related provisions.

[0046] As mentioned in the background art, to improve the service quality of products, after an application is launched, feedback information of users is generally collected and analyzed to optimize the functions of the application according to the feedback information of users.

[0047] In the related art, the feedback information of users is generally analyzed based on manual methods, which has problems of low analysis efficiency and inaccurate analysis results.

[0048] Specifically, in order to comprehensively reflect the optimization direction of the product through the feedback information, the feedback data of users is generally obtained periodically, resulting in a large amount of feedback information to be analyzed each time. Therefore, it is difficult to accurately analyze the optimization direction of the product from the massive feedback information based on the manual analysis method, thus unable to effectively optimize the product and affecting the user experience.

[0049] In view of this, the present disclosure provides a data analysis method, device, readable medium and electronic device to solve the above technical problems.

[0050] To facilitate the understanding of this solution, the following further explains the embodiments of the present disclosure with reference to the accompanying drawings.

[0051] Figure 1 is a flowchart of a data analysis method shown according to an exemplary embodiment of the present disclosure. Referring to Figure 1 , this method can be applied to a terminal device and may include the following steps:

[0052] S101: In response to a data analysis instruction input by a user, send the data analysis instruction to a server to trigger the server to obtain interactive feedback data, analyze the interactive feedback data through a data analysis model to obtain an analysis result, and push the analysis result to the terminal device, where the interactive feedback data includes feedback information on interactive functions in an application.

[0053] Among them, the terminal device can be a mobile terminal device, such as a mobile phone, a wearable device or a tablet, etc., or a non-mobile terminal device, such as a desktop computer or a smart TV, etc.

[0054] Among them, the data analysis model can analyze the interaction feedback data by analyzing the data type of the interaction feedback data. Correspondingly, the analysis result can be the data type of the interaction feedback data and the quantity of the interaction feedback data in each data type. It can also be to analyze the processing priority of the interaction feedback data. Correspondingly, the analysis result can be the processing priority of the interaction feedback data. It can also be to analyze the validity of the interaction feedback data. Correspondingly, the analysis result can be the feedback data useful for optimizing the function of the application program. It can be specifically determined according to the actual situation, and the embodiments of the present disclosure do not impose any restrictions on this.

[0055] Exemplarily, this data analysis method can be embedded in the application program of the terminal device. Thus, a function entry for data analysis can be displayed on the display page of the application program. By clicking on this function entry, the data analysis page can be switched to, and by inputting a data analysis instruction on the data analysis page, the input data analysis instruction can be sent to the server. Correspondingly, after receiving this data analysis instruction, the server can input the obtained interaction feedback data into the data analysis model, analyze the semantics of the interaction feedback data through the data analysis model, and count the interaction feedback data with the same semantics to obtain an analysis result, as Figure 2 shown.

[0056] S102: Display the analysis result.

[0057] Through the above technical solution, after the user inputs a data analysis instruction, the data analysis instruction can be sent to the server to trigger the server to obtain interaction feedback data, and the interaction feedback data can be analyzed through the data analysis model to obtain an analysis result of the interaction feedback data. Thus, the interaction feedback data can be automatically analyzed through the data analysis model. Compared with the related art where the feedback information of the user is analyzed based on a manual method, the method for analyzing the interaction feedback data in the present disclosure can improve the analysis efficiency of the interaction feedback data and the accuracy rate of the analysis result.

[0058] In a possible implementation manner, the responding to the data analysis instruction input by the user, sending the data analysis instruction to the server to trigger the server to obtain interaction feedback data, and analyzing the interaction feedback data through the data analysis model to obtain an analysis result, and pushing the analysis result to the terminal device may include:

[0059] In response to a data analysis instruction input by the user for immediate feedback of the analysis result, send the data analysis instruction to the server to trigger the server to immediately obtain interactive feedback data, analyze the interactive feedback data through a data analysis model, and whenever an analysis result is output, push the analysis result to the terminal device, where the data analysis model is used to output the analysis result of the interactive feedback data in a streaming manner;

[0060] Correspondingly, the displaying of the analysis result may include:

[0061] Whenever an analysis result is received, display the analysis result.

[0062] It should be understood that in order to comprehensively reflect the product optimization direction through interactive feedback data, the feedback data of users is generally obtained periodically to analyze and statistically find out the common problems of the product from a large amount of interactive feedback data, so as to optimize the product targeted. Therefore, when immediate feedback of the analysis result is required, the server can, after receiving the data analysis instruction, obtain the interactive feedback data collected between time T and time T - t, and input the obtained interactive feedback data into the data analysis model for analysis. Where time T represents the time when the server receives the data analysis instruction, and t represents the cycle duration.

[0063] In addition, it should be understood that the analysis of the interactive feedback data by the data analysis model generally lasts for a period of time. If the server waits until all analysis results are analyzed and then sends all the analysis results to the client for output display, it will increase the waiting time of the user and affect the user experience. By the above method, when the data analysis model analyzes an analysis result, the server can send the analysis result to the client for output display, so that the user can quickly view the analysis result and improve the user experience.

[0064] In a possible implementation manner, the responding to the data analysis instruction input by the user, sending the data analysis instruction to the server to trigger the server to obtain interactive feedback data, analyzing the interactive feedback data through a data analysis model, obtaining an analysis result, and pushing the analysis result to the terminal device may include:

[0065] In response to a data analysis instruction input by the user for timed feedback of the analysis result, send the data analysis instruction to the server to trigger the server to periodically obtain interactive feedback data, analyze the interactive feedback data through a data analysis model, and when all analysis results are output, push all the analysis results to the terminal device;

[0066] The displaying of the analysis result may include:

[0067] When all the analysis results are received, display all the analysis results.

[0068] Among them, the timing of obtaining the interactive feedback data can be to obtain the interactive feedback data at 10:00 am every Monday, or to obtain the interactive feedback data at 10:00 am every day. Specifically, it can be set according to the actual situation, and the embodiments of the present disclosure do not impose any restrictions on this.

[0069] It should be understood that in this way, the user is not in a hurry to view the analysis results. Therefore, after the data analysis model analyzes all the analysis results, the server can uniformly send all the analysis results to the terminal device, so as to reduce the communication times between the server and the terminal device, reduce the communication overhead, and improve the performance of the server and the terminal device.

[0070] In a possible implementation manner, the analysis result is associated with priority information of the interactive feedback data, and the priority information is used to indicate the processing priority of the interactive feedback data. The displaying of the analysis result may include:

[0071] Display the analysis result according to the priority information associated with the analysis result.

[0072] Among them, the priority information of the interactive feedback data can be obtained by analyzing the semantics of the interactive feedback data, or by detecting whether there are preset words in the interactive feedback data. The embodiments of the present disclosure do not impose any restrictions on this. For example, the urgency of processing each piece of interactive feedback data can be obtained by analyzing the semantics of each piece of interactive feedback data, and then according to the urgency and the pre-set corresponding relationship between the urgency and the priority information, the priority information of each piece of interactive feedback data can be determined.

[0073] Among them, the priority information of the interactive feedback data may include the priority of the interactive feedback data. Thus, displaying the analysis result according to the priority information associated with the analysis result may be to display each analysis result in the order from high to low priority.

[0074] For example, if the priority of analysis result 1 is P3, the priority of analysis result 2 is P1, the priority of analysis result 3 is P0, the priority of analysis result 4 is P2, and the priority of P0 is higher than that of P1, the priority of P1 is higher than that of P2, and the priority of P2 is higher than that of P3. Then, displaying the analysis result according to the priority information associated with the analysis result may be to display analysis result 3 in the first row, analysis result 2 in the second row, analysis result 4 in the third row, and analysis result 1 in the fourth row.

[0075] In a possible implementation manner, displaying the analysis result according to the priority information associated with the analysis result may include:

[0076] Synchronously displaying the analysis result and the priority information associated with the analysis result, where different priority information has different display styles; or, displaying the analysis results with different priority information according to different display styles, and displaying the analysis results with the same priority information according to the same display style.

[0077] Among them, different display styles may be different display fonts, different display colors, or different display backgrounds, which can be specifically determined according to the actual situation, and the embodiments of the present disclosure do not impose any restrictions on this.

[0078] Exemplarily, the priority of the analysis result can be displayed in front of each analysis result, and the priority is identified with different color backgrounds. For example, the priority P0 is identified with a dark gray background, the priority P1 is identified with a gray background, the priority P2 is identified with a light gray background, and the priority P3 is identified with a white background, as Figure 3 shown. Or the analysis result corresponding to the priority P0 is identified with a dark gray background, the analysis result corresponding to the priority P1 is identified with a gray background, the analysis result corresponding to the priority P2 is identified with a light gray background, and the analysis result corresponding to the priority P3 is identified with a white background, as Figure 4 shown.

[0079] Adopting the above solution, different priority information can be distinguished and displayed when displaying the analysis result, or the analysis results with different priority information can be distinguished and displayed. Thus, the interaction feedback data that needs to be processed urgently can be quickly and intuitively determined according to the priority information or the display style of the analysis result, improving the product optimization efficiency.

[0080] In a possible implementation manner, sending the data analysis instruction to the server in response to the user input data analysis instruction may include:

[0081] In response to the data analysis instruction input by the user in the human-machine dialogue interface, sending the data analysis instruction to the server.

[0082] Exemplarily, an input control and a send control can be displayed in the human-machine dialogue interface. By inputting a data analysis instruction in the input control, such as inputting "analyze the interaction feedback data in the previous two weeks", and by clicking the send control, the data analysis instruction is sent to the server. Or, preset data analysis instructions can be displayed in the human-machine dialogue interface, and by clicking the target data analysis instruction, the target data analysis instruction is sent to the server.

[0083] In a possible implementation, the method may further include:

[0084] While sending the data analysis instruction to the server, display the data analysis instruction in the first session party in the human-computer dialogue interface;

[0085] Correspondingly, the displaying of the analysis result may include:

[0086] Display the analysis result in the second session party in the human-computer dialogue interface.

[0087] Exemplarily, as Figure 5 shown, the human-computer interaction interface includes an input area and a display area. The input area displays a sending control "Send". By inputting a data analysis instruction "Analyze the interaction feedback data in the previous two weeks" in the input area and clicking "Send", the data analysis instruction is displayed in the first session party in the display area. When receiving the data analysis result sent by the server, the analysis result is displayed in the second session party in the display area.

[0088] In a possible implementation, the data analysis method may further include:

[0089] In response to the target channel information input by the user in the human-computer dialogue interface, send the target channel information to the server, so that when the server obtains the interaction feedback data, it obtains the data from the data channel corresponding to the target channel information.

[0090] Wherein, the target channel information may be the name or address of a database storing interaction feedback data, or the name of a target application program storing interaction feedback data, etc. The embodiments of the present disclosure do not make any restrictions on this. Exemplarily, the target channel information may be the address of a database for storing a questionnaire. Thus, after receiving the data analysis instruction, the server can obtain the questionnaire from the database corresponding to the database address.

[0091] Wherein, the user interaction feedback data stored in the database or the target application program may be actively obtained from the user, such as by sending a questionnaire to the user. It may also be actively feedback by the user. For example, a feedback button is set in the user interface of the application program, and the user can click the feedback button during use to feedback on problems or suggestions encountered during use, etc.

[0092] Wherein, the data channel corresponding to the target channel information may be one or multiple, and the embodiments of the present disclosure do not make any restrictions on this.

[0093] In the above - mentioned manner, the function configuration can be carried out in the form of a dialogue on the human - machine interaction interface. Compared with the related art where the function is configured based on the configuration page during function configuration, the operation complexity of configuration can be simplified, and the user experience can be further improved.

[0094] Based on the same concept, an embodiment of the present disclosure also provides a data analysis method, which is applied to a server, as Figure 6 shown. The method may include:

[0095] S601: After receiving a data analysis instruction sent by a terminal device, obtain interaction feedback data, where the data analysis instruction is input by a user in the terminal device, and the interaction feedback data includes feedback information on interaction functions in an application program.

[0096] Among them, the interaction feedback data obtained by the server can be interaction feedback data that has not been obtained before, or a preset number of interaction feedback data, or interaction feedback data collected within a specified duration. The embodiments of the present disclosure do not impose any restrictions on this.

[0097] S602: Analyze the interaction feedback data through a data analysis model to obtain an analysis result.

[0098] Among them, the data analysis model analyzing the interaction feedback data can be analyzing the data type of the interaction feedback data. Correspondingly, the analysis result can be the data type of the interaction feedback data and the quantity of interaction feedback data in each data type. It can also be analyzing the processing priority of the interaction feedback data. Correspondingly, the analysis result can be the processing priority of the interaction feedback data. It can also be analyzing the validity of the interaction feedback data. Correspondingly, the analysis result can be feedback data useful for optimizing the functions of the application program. It can be specifically determined according to the actual situation, and the embodiments of the present disclosure do not impose any restrictions on this.

[0099] Exemplarily, 10 pieces of interaction feedback data can be input into the data analysis model, and the semantics of the 10 pieces of interaction feedback data are analyzed through the data analysis model to count the interaction feedback data with the same semantics, and all the statistical results are determined as the analysis result or each statistical result is determined as the analysis result, as Figure 2 shown.

[0100] S603: Push the analysis result to the terminal device so that the terminal device displays the analysis result.

[0101] Through the above technical solution, after receiving the data analysis instruction sent by the terminal device, the interactive feedback data can be obtained, and the interactive feedback data can be analyzed through the data analysis model to obtain the analysis result of the interactive feedback data. Thus, the interactive feedback data can be automatically analyzed through the data analysis model. Compared with the related art, in which the feedback information of the user is analyzed manually, the method for analyzing the interactive feedback data in the present disclosure can improve the analysis efficiency of the interactive feedback data and the accuracy of the analysis result.

[0102] In a possible implementation manner, the data analysis method may further include:

[0103] Determine the processing urgency of the interactive feedback data according to the semantics of the interactive feedback data; determine the priority information of the interactive feedback data according to the preset corresponding relationship between the processing urgency and the priority information, where the preset corresponding relationship is used to represent the corresponding relationship between the processing urgency and the priority information;

[0104] Correspondingly, the pushing the analysis result to the terminal device so that the terminal device displays the analysis result may include:

[0105] Push the priority information and the analysis result to the terminal device in association, so that the terminal device displays the analysis result according to the priority information.

[0106] Among them, displaying the analysis result according to the priority information associated with the analysis result may be to first determine the priority of each analysis result according to the priority information associated with each analysis result, and then display each analysis result in the order from high to low priority, as Figure 3 shown. It may also be to synchronously display the analysis result and the priority information associated with the analysis result, where different priority information has different display styles, as Figure 4 shown. It may also be to display the analysis results with different priority information according to different display styles, and display the analysis results with the same priority information according to the same display style, as Figure 5 shown, and there may also be other display methods, which are not limited in the embodiments of the present disclosure.

[0107] By adopting the above solution, the priority information of the interactive feedback data can be determined according to the semantics of the interactive feedback data, and the priority information and the analysis result are pushed to the terminal device in association, and when the terminal device displays the analysis result, different priority information can be distinguished and displayed, or the analysis results with different priority information can be distinguished and displayed. Thus, according to the priority information or the display style of the analysis result, the interactive feedback data that needs to be processed urgently can be quickly and intuitively determined, and the product optimization efficiency can be improved.

[0108] Based on the same concept, an embodiment of the present disclosure further provides a data analysis device, as Figure 7 shown, the device may include:

[0109] A first sending module 701, configured to, in response to a data analysis instruction, send the data analysis instruction to a server to trigger the server to obtain interaction feedback data, analyze the interaction feedback data through a data analysis model, obtain an analysis result, and push the analysis result to the terminal device, where the interaction feedback data includes feedback information on an interaction function in an application program;

[0110] A first display module 702, configured to display the analysis result.

[0111] In a possible implementation manner, the first sending module 701 may include:

[0112] A first sending unit, configured to, in response to a data analysis instruction input by a user for instantaneously feedbacking an analysis result, send the data analysis instruction to a server to trigger the server to instantaneously obtain interaction feedback data, analyze the interaction feedback data through a data analysis model, and whenever an analysis result is output, push the analysis result to the terminal device, where the data analysis model is used to output an analysis result of the interaction feedback data in a streaming output manner;

[0113] Correspondingly, the first display module 702 may include:

[0114] A first display unit, configured to display the analysis result whenever an analysis result is received.

[0115] In a possible implementation manner, the first sending module 701 may include:

[0116] A second sending unit, configured to, in response to a data analysis instruction input by a user for periodically feedbacking an analysis result, send the data analysis instruction to a server to trigger the server to periodically obtain interaction feedback data, analyze the interaction feedback data through a data analysis model, and when all analysis results are output, push all the analysis results to the terminal device;

[0117] Correspondingly, the first display module 702 may include:

[0118] A second display unit, configured to display all the analysis results when all the analysis results are received.

[0119] In a possible implementation, the analysis result is associated with priority information of the interaction feedback data, and the priority information is used to indicate the processing priority of the interaction feedback data. Accordingly, the first display module may include:

[0120] A third display unit, configured to display the analysis result according to the priority information associated with the analysis result.

[0121] In a possible implementation, the third display unit may include:

[0122] A first display subunit, configured to synchronously display the analysis result and the priority information associated with the analysis result, where different priority information has different display styles; or,

[0123] A second display subunit, configured to display the analysis results with different priority information according to different display styles, and display the analysis results with the same priority information according to the same display style.

[0124] In a possible implementation, the first sending module 701 may include:

[0125] A third sending unit, configured to send the data analysis instruction to the server in response to a data analysis instruction input by a user in the human-computer dialogue interface.

[0126] In a possible implementation, the device may further include:

[0127] A second display module, configured to display the data analysis instruction in a first session party in the human-computer dialogue interface while sending the data analysis instruction to the server;

[0128] Accordingly, the first display module 702 may include:

[0129] A fourth display unit, configured to display the analysis result in a second session party in the human-computer dialogue interface.

[0130] In a possible implementation, the device may further include:

[0131] A second sending module, configured to send the target channel information to the server in response to the target channel information input by the user in the human-computer dialogue interface, so that when the server acquires the interaction feedback data, it acquires the data from the data channel corresponding to the target channel information.

[0132] Based on the same concept, an embodiment of the present disclosure further provides a data analysis device, as Figure 8 shown, the device may include:

[0133] An acquisition module 801, configured to acquire interactive feedback data in response to a data analysis instruction, where the data analysis instruction is sent by a terminal device in response to the data analysis instruction, and the interactive feedback data includes feedback information on an interactive function in an application program;

[0134] An analysis module 802, configured to analyze the interactive feedback data through a data analysis model to obtain an analysis result;

[0135] A push module 803, configured to push the analysis result to the terminal device so that the terminal device displays the analysis result.

[0136] In a possible implementation manner, the device may further include:

[0137] A first determination module, configured to determine the processing urgency of the interactive feedback data according to the semantics of the interactive feedback data;

[0138] A second determination module, configured to determine priority information of the interactive feedback data according to a preset corresponding relationship, where the preset corresponding relationship is used to represent the corresponding relationship between the processing urgency and the priority information;

[0139] Correspondingly, the push module 803 is configured to: push the priority information and the analysis result to the terminal device in an associated manner so that the terminal device displays the analysis result according to the priority information.

[0140] Based on the same concept, an embodiment of the present disclosure further provides a computer-readable medium, on which a computer program is stored, and when the program is executed by a processing device, the steps of the method described in any one of the first aspects are implemented.

[0141] Based on the same concept, an embodiment of the present disclosure further provides an electronic device, which may include:

[0142] A storage device, on which a computer program is stored;

[0143] A processing device, configured to execute the computer program in the storage device to implement the steps of the method described in any one of the first aspects.

[0144] Next, refer to Figure 9 , which shows a schematic structural diagram of an electronic device 900 suitable for implementing an 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), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc.Figure 9 The electronic device shown is merely an example and should not impose any limitations on the functions and scope of use of the embodiments of the present disclosure.

[0145] As Figure 9 shown, the electronic device 900 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 901, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 902 or the program loaded from the storage device 908 into the random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the electronic device 900 are also stored. The processing device 901, the ROM 902, and the RAM 903 are connected to each other through a bus 904. The input / output (I / O) interface 905 is also connected to the bus 904.

[0146] Generally, the following devices may be connected to the I / O interface 905: an input device 906 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 907 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 908 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 909. The communication device 909 may allow the electronic device 900 to communicate with other devices wirelessly or wiredly to exchange data. Although Figure 9 the electronic device 900 with various devices is shown, it should be understood that it is not required to implement or have all the shown devices. Instead, more or fewer devices may be implemented or had.

[0147] Specifically, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, the embodiments of the present disclosure include a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from the network through the communication device 909, or installed from the storage device 908, or installed from the ROM 902. When the computer program is executed by the processing device 901, the above-mentioned functions defined in the methods of the embodiments of the present disclosure are executed.

[0148] It should be noted that the above-mentioned computer-readable medium in the present disclosure can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can 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, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present disclosure, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, in which the computer-readable program code is carried. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and this computer-readable signal medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0149] In some embodiments, communication can be carried out using any currently known or future-developed network protocol such as HTTP (HyperText Transfer Protocol), and can be interconnected with digital data communication in any form or medium (for example, a communication network). Examples of communication networks include local area networks ("LAN"), wide area networks ("WAN"), the Internet (for example, the Internet), and end-to-end networks (for example, ad hoc end-to-end networks), as well as any currently known or future-developed networks.

[0150] The above-mentioned computer-readable medium can be included in the above-mentioned electronic device; it can also exist separately without being assembled into the electronic device.

[0151] The above computer-readable medium stores one or more programs which, when executed by the electronic device, cause the electronic device to: in response to a data analysis instruction input by a user, send the data analysis instruction to a server to trigger the server to obtain interactive feedback data, analyze the interactive feedback data through a data analysis model to obtain an analysis result, and push the analysis result to the terminal device, where the interactive feedback data includes feedback information on an interactive function in an application program; and display the analysis result.

[0152] Alternatively, the above computer-readable medium stores one or more programs which, when executed by the electronic device, cause the electronic device to: after receiving a data analysis instruction sent by a terminal device, obtain interactive feedback data, where the data analysis instruction is input by a user in the terminal device, and the interactive feedback data includes feedback information on an interactive function in an application program; analyze the interactive feedback data through a data analysis model to obtain an analysis result; and push the analysis result to the terminal device so that the terminal device displays the analysis result.

[0153] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages or combinations thereof. The programming languages include, but are not limited to, object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the 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., via the Internet using an Internet service provider).

[0154] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or by a combination of dedicated hardware and computer instructions.

[0155] The modules described in the embodiments of the present disclosure can be implemented in software or in hardware. In some cases, the name of the module does not constitute a limitation on the module itself.

[0156] The functions described above herein can be performed, at least in part, by one or more hardware logic components. By way of example, and 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 a chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0157] In the context of the present disclosure, a machine-readable medium may be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. 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, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0158] The above description is only a preferred embodiment of the present disclosure and an explanation of the applied technical principles. 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 the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the present disclosure.

[0159] In addition, although the operations are depicted in a particular order, this should not be construed as requiring that the operations be performed in the particular order shown or in sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, although a number of specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features described in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, the various features described in the context of a single embodiment may also be implemented separately or in any suitable sub-combination in multiple embodiments.

[0160] Although the subject matter has been described in language specific to structural features and / or methodological logical acts, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. On the contrary, the specific features and acts described above are merely example forms for implementing the claims. Regarding the apparatus in the above embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments related to the method, and will not be elaborated herein.

Claims

1. A data analysis method, characterized in that, Applied to a terminal device, the method includes: In response to a data analysis instruction input by a user, sending the data analysis instruction to a server to trigger the server to obtain interaction feedback data, and analyzing the interaction feedback data through a data analysis model to obtain an analysis result, and pushing the analysis result to the terminal device, where the interaction feedback data includes feedback information on interaction functions in an application program; Displaying the analysis result.

2. The data analysis method according to claim 1, characterized in that, The step of "In response to a data analysis instruction input by a user, sending the data analysis instruction to a server to trigger the server to obtain interaction feedback data, and analyzing the interaction feedback data through a data analysis model to obtain an analysis result, and pushing the analysis result to the terminal device" includes: In response to a data analysis instruction input by a user for instant feedback of an analysis result, sending the data analysis instruction to the server to trigger the server to instantaneously obtain interaction feedback data, analyzing the interaction feedback data through a data analysis model, and whenever an analysis result is output, pushing the analysis result to the terminal device, where the data analysis model is used to output the analysis result of the interaction feedback data in a streaming output manner; The step of "Displaying the analysis result" includes: Whenever an analysis result is received, displaying the analysis result.

3. The data analysis method according to claim 1, characterized in that, The step of "In response to a data analysis instruction input by a user, sending the data analysis instruction to a server to trigger the server to obtain interaction feedback data, and analyzing the interaction feedback data through a data analysis model to obtain an analysis result, and pushing the analysis result to the terminal device" includes: In response to a data analysis instruction input by a user for timed feedback of an analysis result, sending the data analysis instruction to the server to trigger the server to periodically obtain interaction feedback data, analyzing the interaction feedback data through a data analysis model, and when all analysis results are output, pushing all the analysis results to the terminal device; The step of "Displaying the analysis result" includes: When all the analysis results are received, displaying all the analysis results.

4. The data analysis method according to any one of claims 1-3, characterized in that, The analysis result is associated with priority information of the interaction feedback data, and the priority information is used to indicate the processing priority of the interaction feedback data. The step of "Displaying the analysis result" includes: Displaying the analysis result according to the priority information associated with the analysis result.

5. The data analysis method according to claim 4, characterized in that, The step of "Displaying the analysis result according to the priority information associated with the analysis result" includes: Synchronously displaying the analysis result and the priority information associated with the analysis result, where different priority information has different display styles; or Displaying the analysis results with different priority information in different display styles, and displaying the analysis results with the same priority information in the same display style.

6. The data analysis method according to any one of claims 1-3, characterized in that, The step of "In response to a data analysis instruction input by a user, sending the data analysis instruction to a server" includes: In response to a data analysis instruction input by a user in a human-machine dialogue interface, send the data analysis instruction to a server.

7. The data analysis method according to claim 6, characterized in that, The method further includes: While sending the data analysis instruction to the server, display the data analysis instruction in a first conversation party in the human-machine dialogue interface; The displaying the analysis result includes: Display the analysis result in a second conversation party in the human-machine dialogue interface.

8. The data analysis method according to claim 6, characterized in that, The data analysis method further includes: In response to target channel information input by the user in the human-machine dialogue interface, send the target channel information to the server, so that when the server obtains the interaction feedback data, it obtains the data from the data channel corresponding to the target channel information.

9. A data analysis method, characterized in that, Applied to a server, the method includes: After receiving a data analysis instruction sent by a terminal device, obtain interaction feedback data, where the data analysis instruction is input by a user in the terminal device, and the interaction feedback data includes feedback information on an interaction function in an application program; Analyze the interaction feedback data through a data analysis model to obtain an analysis result; Push the analysis result to the terminal device so that the terminal device displays the analysis result.

10. The data analysis method according to claim 9, characterized in that, The data analysis method further includes: Determine the processing urgency of the interaction feedback data according to the semantics of the interaction feedback data; Determine the priority information of the interaction feedback data according to the preset corresponding relationship between the processing urgency and the priority information, where the preset corresponding relationship is used to represent the corresponding relationship between the processing urgency and the priority information; The pushing the analysis result to the terminal device so that the terminal device displays the analysis result includes: Associate and push the priority information with the analysis result to the terminal device so that the terminal device displays the analysis result according to the priority information.

11. A data analysis device, characterized in that, The device includes: A first sending module, configured to send the data analysis instruction to a server in response to a data analysis instruction input by a user, so as to trigger the server to obtain interaction feedback data, analyze the interaction feedback data through a data analysis model to obtain an analysis result, and push the analysis result to the terminal device, where the interaction feedback data includes feedback information on an interaction function in an application program; A first display module, configured to display the analysis result.

12. A data analysis device, characterized in that, The device includes: An obtaining module, configured to obtain interaction feedback data after receiving a data analysis instruction sent by a terminal device, where the data analysis instruction is input by a user in the terminal device, and the interaction feedback data includes feedback information on an interaction function in an application program; An analysis module, configured to analyze the interaction feedback data through a data analysis model to obtain an analysis result; A pushing module, configured to push the analysis result to a terminal device so that the terminal device displays the analysis result.

13. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by a processing device, it implements the steps of the method according to any one of claims 1-10.

14. An electronic device, characterized in that, Includes: A storage device, on which a computer program is stored; A processing device for executing the computer program in the storage device to implement the steps of the method according to any one of claims 1-10.

Images