Account evaluation method and device, storage medium and electronic device

Abstract

The application discloses an account evaluation method and device, a storage medium and an electronic device. It relates to the field of financial technology, and the method comprises the following steps: obtaining operation behavior data of a target account on N terminals, wherein N is an integer greater than or equal to 2; determining a first parameter value based on the operation behavior data of the target account on the N terminals, wherein the first parameter value is used to indicate the similarity between the operation behaviors of the target account on the N terminals; determining whether the first parameter value is in a preset first numerical interval; and if the first parameter value is in the preset first numerical interval, determining an evaluation result of the target account based on the operation behavior data of the target account on the N terminals. Through the application, the technical problem of low accuracy and poor applicability of the account evaluation method based on a single terminal in the related art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of financial technology, in particular to an account evaluation method and device, a storage medium and an electronic device. BACKGROUND

[0002] In computers, mobile phones, tablets (PAD) and other multi-terminals, the account rating system of the same account is becoming increasingly important. The rating not only represents the adhesion of the account to the system, but also can reverse the dependence and frequency of use of the account on the system through a reasonably set rating system. In related technologies, when performing account evaluation, the operation behavior data recorded in a single terminal is mainly used for account evaluation, which ignores the possible differences in account behavior in different terminals, thereby resulting in low accuracy of the account evaluation result and difficulty in effectively applying to all terminals.

[0003] For the above-mentioned problem of low accuracy and poor applicability of the account evaluation method based on a single terminal in related technologies, no effective solution has been proposed so far. SUMMARY

[0004] The main purpose of the present application is to provide an account evaluation method, device, storage medium and electronic device to solve the problem of low accuracy and poor applicability of the account evaluation method based on a single terminal in related technologies.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, an account evaluation method is provided, which comprises: obtaining operation behavior data of a target account in N terminals respectively, wherein N is an integer greater than or equal to 2; determining a first parameter value based on the operation behavior data of the target account in the N terminals respectively, wherein the first parameter value is used to indicate the similarity between the operation behavior of the target account in the N terminals respectively; judging whether the first parameter value is in a preset first numerical interval; if the first parameter value is in the preset first numerical interval, determining an evaluation result of the target account based on the operation behavior data of the target account in the N terminals respectively.

[0006] Optionally, the method further comprises: if the first parameter value is in a preset second numerical interval, determining a first terminal from the N terminals, wherein a similarity between the operation behavior data of the target account in the first terminal and the operation behavior data of the target account in other terminals is less than a preset similarity threshold, wherein the other terminals are terminals other than the first terminal in the N terminals, and a lower limit value of the preset first numerical interval is greater than or equal to a lower limit value of the preset second numerical interval; determining a second parameter value corresponding to the first terminal based on the operation behavior data of the M accounts corresponding to the first terminal, wherein the second parameter value is used to indicate the similarity between the operation behaviors of the accounts included in the first terminal, and M is an integer greater than or equal to 2; determining whether the second parameter value is in a preset third numerical interval; if the second parameter value is in the preset third numerical interval, determining new operation behavior data of the target account in the first terminal based on the operation behavior data of the M accounts corresponding to the first terminal; and determining the evaluation result of the target account based on the operation behavior data of the target account in the other terminals and the new operation behavior data of the target account in the first terminal.

[0007] Optionally, the method further comprises: if the second parameter value is in a preset fourth numerical interval, determining preset operation behavior data as the new operation behavior data of the target account in the first terminal, wherein a lower limit value of the preset third numerical interval is greater than or equal to an upper limit value of the preset fourth numerical interval; and determining the evaluation result of the target account based on the operation behavior data of the target account in the other terminals and the new operation behavior data of the target account in the first terminal.

[0008] Optionally, the determining of the new operation behavior data of the target account in the first terminal based on the operation behavior data of the M accounts corresponding to the first terminal comprises: calculating an average value of the operation behavior data of the M accounts corresponding to the first terminal; and determining the new operation behavior data of the target account in the first terminal according to the average value.

[0009] Optionally, the determining of the evaluation result of the target account based on the operation behavior data of the target account in the N terminals comprises: determining a comprehensive operation behavior score of the target account based on the operation behavior data of the target account in the N terminals; and determining the evaluation result of the target account based on the comprehensive operation behavior score.

[0010] Optionally, the determining the comprehensive operation behavior score of the target account based on the operation behavior data of the target account at the N terminals comprises: determining the operation behavior data of the target account at the N terminals; determining weight values corresponding to the N terminals respectively; and obtaining the comprehensive operation behavior score based on the operation behavior data of the target account at the N terminals and the weight values corresponding to the N terminals respectively.

[0011] Optionally, the determining the evaluation result of the target account based on the comprehensive operation behavior score comprises: obtaining a preset database, wherein a plurality of operation behavior score intervals and behavior levels corresponding to the plurality of operation behavior score intervals are stored in the preset database; determining a target operation behavior score interval to which the comprehensive operation behavior score belongs; determining a target behavior level corresponding to the target operation behavior score interval from the preset database; and determining the evaluation result of the target account according to the target behavior level.

[0012] To achieve the above object, according to another aspect of the present application, an account evaluation device is provided, which comprises: a first obtaining module configured to obtain operation behavior data of a target account at N terminals respectively, wherein N is an integer greater than or equal to 2; a first determining module configured to determine a first parameter value based on the operation behavior data of the target account at the N terminals respectively, wherein the first parameter value is used to indicate a similarity between operation behaviors of the target account at the N terminals respectively; a first judging module configured to judge whether the first parameter value is in a preset first numerical interval; and a second determining module configured to determine an evaluation result of the target account based on the operation behavior data of the target account at the N terminals respectively, if the first parameter value is in the preset first numerical interval.

[0013] To achieve the above object, according to another aspect of the present application, a non-volatile storage medium is also provided, which stores a plurality of instructions, the instructions being adapted to be loaded and executed by a processor to implement any one of the account evaluation methods.

[0014] To achieve the above object, according to another aspect of the present application, an electronic device is also provided, which comprises one or more processors and a memory, the memory being configured to store one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement any one of the account evaluation methods.

[0015] According to the application, the following steps are adopted: obtaining operation behavior data of a target account on N terminals respectively, wherein N is an integer greater than or equal to 2; determining a first parameter value based on the operation behavior data of the target account on the N terminals respectively, wherein the first parameter value is used to indicate the similarity between the operation behaviors of the target account on the N terminals respectively; judging whether the first parameter value is in a preset first numerical interval; if the first parameter value is in the preset first numerical interval, determining an evaluation result of the target account based on the operation behavior data of the target account on the N terminals respectively, thereby achieving the purpose of accurately evaluating the account behavior by comprehensively analyzing the operation behavior data of multiple terminals, realizing the technical effect of improving the accuracy and applicability of account evaluation, and further solving the technical problems of low accuracy and poor applicability of the account evaluation method based on a single terminal in the related art. BRIEF DESCRIPTION OF DRAWINGS

[0016] The accompanying drawings, which form a part of this application, are included to provide a further understanding of the application and are incorporated in and constitute a part of this application. The embodiments of this application, and their

[0017] Figure 1 is a schematic diagram of an account evaluation method according to an embodiment of the application;

[0018] Figure 2 is a flowchart of an optional first parameter value judgment according to an embodiment of the application;

[0019] Figure 3 is a flowchart of an optional second parameter value judgment according to an embodiment of the application;

[0020] Figure 4 is a schematic diagram of an optional account level interaction system according to an embodiment of the application;

[0021] Figure 5 is a flowchart of an optional same account in an office system multi-terminal account experience analysis according to an embodiment of the application;

[0022] Figure 6 is a flowchart of an optional different account in an office system same-terminal account experience analysis according to an embodiment of the application;

[0023] Figure 7 is a schematic diagram of an account evaluation device according to an embodiment of the application.

[0024] Figure 8 is a schematic diagram of an electronic device provided according to an embodiment of the application. DETAILED DESCRIPTION

[0025] It should be noted that the embodiments and features in the present application can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0026] In order for those skilled in the technical field to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0027] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product or device.

[0028] It should be noted that the relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, analyzed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties. For example, an interface is provided between the system and the relevant user or institution. Before obtaining the relevant information, the interface needs to send a request to the aforementioned user or institution, and after receiving the consent information feedback from the aforementioned user or institution, the relevant information is obtained.

[0029] The present application will be described below in conjunction with the preferred implementation steps, Figure 1 is a flowchart of the account evaluation method according to an embodiment of the present application, as Figure 1 shown, the method comprises the following steps:

[0030] Step S102, obtaining the operation behavior data of the target account on N terminals respectively, wherein N is an integer greater than or equal to 2.

[0031] Optionally, the terminal includes a computer terminal, a mobile phone terminal, a mobile PAD terminal, and the like. The operation behavior data includes attendance clock-in, an email, instant messaging software, learning records, and the like. The operation behavior data of the target account on different terminals is used to determine the evaluation result of the target account, which can effectively improve the accuracy of the account evaluation.

[0032] In step S104, a first parameter value is determined based on the operation behavior data of the target account on the N terminals, wherein the first parameter value is used to indicate the similarity between the operation behaviors of the target account on the N terminals.

[0033] Optionally, the first parameter value is the operation behavior data of the same account on different clients and different office functions, which can be, but is not limited to, an availability value. The availability value can be calculated based on a variance, for example, taking the clock-in as an example. The clock-in times of the target account on the N terminals (such as a computer terminal, a mobile phone terminal, and a mobile PAD terminal) are determined, and the clock-in time corresponding to each clock-in is determined. The average clock-in time of the target account on the N terminals is calculated based on the clock-in times of the target account on the N terminals and the clock-in time corresponding to each clock-in. The difference or standard deviation of the average clock-in time of the target account on the N terminals is determined. The variance or standard deviation is recorded as the availability value, which is used to indicate the similarity between the clock-in times of the target account on the N terminals. If the first parameter value is larger, it indicates that the similarity between the operation behaviors of the target account on the N terminals is higher. If the first parameter value is smaller, it indicates that the similarity between the operation behaviors of the target account on the N terminals is lower.

[0034] In step S106, it is determined whether the first parameter value is in a preset first numerical interval.

[0035] Optionally, the first numerical interval is an interval close to the maximum value of the first parameter. For example, if the maximum value of the first parameter is 20, the first numerical interval can be [19.5, 20]. The operation behavior data of the target account is determined, and the evaluation result of the target account can be accurately determined based on the operation behavior data of the target account.

[0036] In step S108, if the first parameter value is in the preset first numerical interval, the evaluation result of the target account is determined based on the operation behavior data of the target account on the N terminals.

[0037] Optionally, if the first parameter value is in the preset first numerical interval, it indicates that the similarity between the operation behaviors of the target account on the N terminals is higher. Therefore, the evaluation result of the target account is determined based on the operation behavior data of the target account on the N terminals. Figure 2is a flow chart of an optional first parameter value judgment according to an embodiment of the present application, as shown Figure 2 The operation behavior data of the target account in N terminals is obtained, the first parameter value is set as the availability value R of the account experience behavior feedback experience value, the minimum value of the availability value is set as 0, and the maximum value is set as 2R. When the first parameter value is close to 2R, the office system includes the operation behavior of the account into the primary judgment data, determines the evaluation result of the target account according to the operation behavior data, and displays the corresponding title information of the target account.

[0038] In an optional embodiment, if the first parameter value is in a preset second numerical interval, a first terminal is determined from the N terminals, wherein the similarity between the operation behavior data of the target account in the first terminal and the operation behavior data of the target account in other terminals is less than a preset similarity threshold, the other terminals are terminals other than the first terminal in the N terminals, the lower limit value of the preset first numerical interval is greater than or equal to the upper limit value of the preset second numerical interval; based on the operation behavior data of the M accounts corresponding to the first terminal, a second parameter value corresponding to the first terminal is determined, wherein the second parameter value is used to indicate the similarity between the operation behaviors of the accounts included in the first terminal, and M is an integer greater than or equal to 2; it is judged whether the second parameter value is in a preset third numerical interval; if the second parameter value is in the preset third numerical interval, the new operation behavior data of the target account in the first terminal is determined based on the operation behavior data of the M accounts corresponding to the first terminal; the evaluation result of the target account is determined based on the operation behavior data of the target account in the other terminals and the new operation behavior data of the target account in the first terminal.

[0039] Optionally, the second numerical interval is an interval close to the minimum value of the first parameter, for example, the minimum value of the second parameter is set as 0, and the second numerical interval can be (0, 0.05]. If the first parameter value is in the preset second numerical interval, it indicates that the similarity between the operation behaviors of the target account in the N terminals is low, and the first terminal with the greatest difference between the operation behavior data of other terminals is determined from the N terminals. Based on the operation behavior data of the M accounts corresponding to the first terminal, the second parameter value corresponding to the first terminal is determined. As shown in Figure 2 When the first parameter value is close to 0, the virtual digital human system does not process the archiving and cross analyzes the operation behavior data of the remaining accounts with the same behavior.

[0040] Optionally, the second parameter value is a similarity behavior value of the same operation of the same terminal and different accounts, which can be but is not limited to a retention rate value. The retention rate value can be but is not limited to calculated based on variance. For example, taking the case of M accounts performing work clock-in on a computer as an example, the number of clock-in times of the M accounts (such as account 1, account 2, and account 3) on the computer is determined, and the clock-in time corresponding to each clock-in time is determined. Based on the number of clock-in times of the M accounts on the computer and the clock-in time corresponding to each clock-in time, the average clock-in time corresponding to each of the M accounts is calculated, and the variance or standard deviation of the average clock-in time corresponding to each of the M accounts is calculated. The variance or standard deviation is recorded as the retention rate value, which is used to indicate the similarity between the operation behaviors of the accounts included in the first terminal. If the second parameter value is larger, it indicates that the same operation behavior of the terminal is accepted by more accounts. If the second parameter value is smaller, it indicates that the operation behavior of the terminal does not conform to the operation habits of most accounts.

[0041] Optionally, in the case that the first parameter value is in a preset second numerical interval, it is determined whether the second parameter value is in a preset third numerical interval. If the second parameter value is in the preset third numerical interval, it indicates that the similarity between the operation behaviors of the M accounts corresponding to the first terminal is high. Then, the operation behavior data of the M accounts corresponding to the first terminal is determined as new operation behavior data of the target account in the first terminal. Based on the operation behavior data of the target account in other terminals and the new operation behavior data of the target account in the first terminal, the evaluation result of the target account is determined. Figure 3 is a flowchart of an optional second parameter value judgment according to an embodiment of the present application, as shown in Figure 3 The operation behavior data of different accounts of the first terminal is obtained. The second parameter value is set as a retention rate value A. The minimum value of the availability value is set as 0, and the maximum value is set as 2A. If the second parameter value is close to 2A, the operation behavior data of different accounts corresponding to the first terminal is determined as new operation behavior data of the target account in the first terminal.

[0042] In an optional embodiment, if the above-mentioned second parameter value is in a preset fourth numerical interval, the preset operation behavior data is determined as the new operation behavior data of the target account in the first terminal. The lower limit value of the preset third numerical interval is greater than or equal to the upper limit value of the preset fourth numerical interval. Based on the operation behavior data of the target account in other terminals and the new operation behavior data of the target account in the first terminal, the evaluation result of the target account is determined.

[0043] Optionally, if the second parameter value is in a preset fourth numerical interval, indicating that the similarity between the operation behaviors of the corresponding M accounts in the first terminal is low, the preset operation behavior data is determined as the new operation behavior data of the target account in the first terminal, wherein the preset operation behavior data represents the average operation behavior data of the corresponding M accounts in the first terminal, and then the evaluation result of the target account is determined based on the operation behavior data of the target account in other terminals and the new operation behavior data of the target account in the first terminal. As shown in Figure 3 If the second parameter value is close to 0, the preset operation behavior data is taken as the average operation behavior data of the corresponding M accounts in the first terminal.

[0044] In an optional embodiment, the determination of the new operation behavior data of the target account in the first terminal based on the operation behavior data of the corresponding M accounts in the first terminal includes: calculating the average value of the operation behavior data of the corresponding M accounts in the first terminal; and determining the new operation behavior data of the target account in the first terminal according to the average value.

[0045] Optionally, since the similarity between the operation behaviors of the corresponding M accounts in the first terminal is low, the average value of the operation behavior data of the corresponding M accounts in the first terminal is taken as the new operation behavior data of the target account in the first terminal. This method replaces the abnormal value with the average value, so that the accuracy of the account evaluation can be further improved.

[0046] In an optional embodiment, the determination of the evaluation result of the target account based on the operation behavior data of the target account in the N terminals includes: determining a comprehensive operation behavior score of the target account based on the operation behavior data of the target account in the N terminals; and determining the evaluation result of the target account based on the comprehensive operation behavior score.

[0047] Optionally, the comprehensive operation behavior score of the target account is determined based on the operation behavior data of the target account in the N terminals, and then the evaluation result of the target account is determined according to the comprehensive operation behavior score, so as to ensure the accuracy of the evaluation result of the target account.

[0048] In an optional embodiment, the determination of the comprehensive operation behavior score of the target account based on the operation behavior data of the target account in the N terminals includes: determining the operation behavior data of the target account in the N terminals; determining a weight value corresponding to each of the N terminals; and obtaining the comprehensive operation behavior score based on the operation behavior data of the target account in the N terminals and the weight value corresponding to each of the N terminals.

[0049] Optionally, based on the operation behavior data of the target account on the N terminals respectively, the weight values corresponding to the N terminals respectively are determined, wherein the weight values can be the same or different, the product of the operation behavior data of the target account on the N terminals respectively and the weight values corresponding to the N terminals respectively is calculated to obtain the comprehensive operation behavior score. By assigning different weights to the operation behavior data of the target account on the N terminals respectively, important operation behavior data can be given greater weight, so that the comprehensive operation behavior score can be obtained more accurately.

[0050] In an optional embodiment, the above determining the evaluation result of the target account based on the comprehensive operation behavior score comprises: obtaining a preset database, wherein the preset database stores a plurality of operation behavior score intervals and behavior levels corresponding to the plurality of operation behavior score intervals respectively; determining a target operation behavior score interval to which the comprehensive operation behavior score belongs; determining a target behavior level corresponding to the target operation behavior score interval from the preset database; and determining the evaluation result of the target account according to the target behavior level.

[0051] Optionally, a database storing a plurality of operation behavior score intervals and behavior levels corresponding to the plurality of operation behavior score intervals respectively is constructed in advance, a target operation behavior score interval to which the comprehensive operation behavior score belongs is determined, a target behavior level corresponding to the target operation behavior score interval is determined from the preset database, and the evaluation result of the target account is determined according to the target behavior level. By this method, the target behavior level corresponding to the target operation behavior score interval can be matched automatically by using the preset database, and the evaluation result of the target account can be obtained.

[0052] In an optional embodiment, after the evaluation result of the target account is determined, the method further comprises: determining an information push result corresponding to the target account based on the evaluation result of the target account, wherein the information push result comprises at least one push content and a push time corresponding to the at least one push content respectively, and the at least one push content comprises at least one of the following: weather forecast, traffic condition, personal reminder, news digest, work arrangement, and health tips.

[0053] Through the above mode, the information is pushed in combination with the evaluation of the target account, the purpose of targeted information pushing for the user can be achieved, and the user experience is improved. Taking the working clock-in behavior as an example, the operation behavior data of N terminals is the working opening time of the target account at the N terminals, and the corresponding output evaluation result of the target account is "the clock-in time is earlier than 80% of the users". According to the above evaluation result, the target account can be pushed weather forecast, traffic condition, personal reminder, news digest, work arrangement, health tips and the like, and the push time of each push content can be determined according to the evaluation result of the clock-in time of the target account. For example, for the weather forecast: according to the early or late of the working clock-in time, the weather of the day can be pushed to remind the target account whether to take an umbrella or pay attention to the dress. For the traffic condition: according to the traffic condition of the location of the target account, whether there is road congestion or traffic accident can be informed to the target account in advance, so that the target account can adjust the travel plan. For the personal reminder: according to the personal habit and demand of the target account, the reminder items before work can be pushed, such as a cup of coffee to refresh, preparation of files or conference materials and the like. For the news digest: according to the working clock-in time of the target account, the important news digest of the day can be pushed to let the target account know the latest dynamics at home and abroad. For the work arrangement: according to the work schedule of the target account, the work arrangement and important tasks of the day can be pushed in advance, so that the target account can prepare and arrange work in time. For the health tips: according to the working clock-in time of the target account, some health tips can be pushed, such as stretching exercise after getting up in the morning, healthy breakfast pushing and the like, to help the target account keep healthy.

[0054] Through the above steps S102 to S108, the purpose of accurately evaluating the account behavior evaluation result by comprehensively combining the operation behavior data of multiple terminals can be achieved, so that the technical effect of improving the accuracy and applicability of the account evaluation is realized, and the technical problems of low accuracy and poor applicability of the account evaluation based on a single terminal in the related art are solved.

[0055] Based on the above embodiments and optional embodiments, the present application proposes an optional implementation method, which comprises:

[0056] Step S1, operation behavior data of a target account at N terminals is obtained, wherein N is an integer greater than or equal to 2.

[0057] Step S2, a first parameter value is determined based on the operation behavior data of the target account at the N terminals.

[0058] Step S3, it is judged whether the first parameter value is in a preset first numerical interval.

[0059] Step S4, if the first parameter value is in a preset first numerical interval, step S10 is executed, otherwise step S5 is executed.

[0060] Step S5, if the first parameter value is in a preset second numerical interval, a first terminal with the greatest difference between the operation behavior data of other terminals is determined from the N terminals.

[0061] Step S6, based on the operation behavior data of the M accounts corresponding to the first terminal, a second parameter value corresponding to the first terminal is determined, wherein M is an integer greater than or equal to 2.

[0062] Step S7, determine whether the second parameter value is in a preset third numerical interval.

[0063] Step S8, if the second parameter value is in a preset third parameter threshold, the average value of the operation behavior data of the M accounts corresponding to the first terminal is calculated, and the average value is taken as the new operation behavior data of the target account in the first terminal, and step S10 is executed, then step S9 is executed.

[0064] Step S9, if the second parameter value is in a preset fourth parameter threshold, the preset operation behavior data is determined as the new operation behavior data of the target account in the first terminal.

[0065] Step S10, based on the operation behavior data of the target account in the N terminals respectively, the weight value corresponding to the N terminals respectively is determined.

[0066] Step S11, the product of the operation behavior data of the target account in the N terminals respectively and the corresponding weight value is calculated to obtain a comprehensive operation behavior score.

[0067] Step S12, a preset database is established, wherein the preset database stores a plurality of operation behavior score intervals and a plurality of behavior levels corresponding to the plurality of operation behavior score intervals respectively.

[0068] Step S13, determine the target operation behavior score interval to which the comprehensive operation behavior score belongs.

[0069] Step S14, the target behavior level corresponding to the target operation behavior score interval is determined from the preset database, and the evaluation result of the target account is determined according to the target behavior level.

[0070] Based on the above embodiments and optional embodiments, another optional office system virtual digital person account level determination interactive system is proposed, as shown in Figure 4 Figure 4 ​is a schematic diagram of an optional account level interaction system according to an embodiment of the present application, and specifically comprises: a same account in an office system multi-end account experience behavior characteristic extraction module, a different account in an office system same end account experience behavior characteristic extraction module, and a level information / title / image display module. Figure 5 is a flowchart of an optional same account in an office system multi-end account experience analysis according to an embodiment of the present application, as shown in Figure 5 The same account in an office system multi-end account experience behavior characteristic extraction module can implement the following method steps, as shown in

[0071] Step S21, based on the operation behavior data of the account when using the same function at different office terminals (computer terminal, mobile phone terminal, mobile PAD terminal, etc.).

[0072] Step S22, based on the behavior habits of the account in different function modules (real-time communication module, point-to-point information transmission module, attendance clock-in module, learning and examination module, etc.) in the office system, extract the account behavior characteristics.

[0073] Step S23, receive information and obtain the information corresponding to the account experience.

[0074] Step S24, extract the information corresponding to the account experience analyzed by the system.

[0075] Step S25, according to the analysis information result, provide the level information, title, and figure most suitable for the account by the virtual digital person, and form the operation behavior account experience method unique to the account.

[0076] Step S26, extract the different characteristics of the account difference office system operation behavior, and revise the behavior of the account with average operation behavior data.

[0077] Figure 6 is a flowchart of an optional same account in an office system multi-end account experience analysis according to an embodiment of the present application, as shown in Figure 6 The same account in an office system multi-end account experience behavior characteristic extraction module can implement the following method steps, as shown in

[0078] Step S31, based on the same terminal (computer terminal, mobile phone terminal, mobile PAD terminal, etc.), extract the operation behavior data of different accounts using the same device in the office system.

[0079] Step S32, based on the behavior habits of different accounts in the same function module (real-time communication module, point-to-point information transmission module, attendance clock-in module, learning and examination module, etc.) in the office system, extract the account behavior characteristics.

[0080] Step S33, receive information and obtain the information corresponding to the account experience.

[0081] Step S34, extract the information corresponding to the account experience analyzed by the system.

[0082] Step S35, according to the analysis information result, the virtual digital person provides the most suitable level information, title, figure corresponding to the account, forms the account experience method of the operation behavior of the account under the same terminal and the same behavior.

[0083] Step S36, extract the different characteristics of the account differentiation office system operation behavior, and revise the behavior of the account with the average operation behavior data.

[0084] The office end virtual digital person in the level information / title / figure display module will display the level information / title / figure corresponding to the account on the page, and will feed back the behavior of the favorite and regular operation of the different accounts in the same end to the system. After that, the system will adjust the interactive experience corresponding to the behavior / title / level, and provide the most close account experience behavior for the corresponding account.

[0085] The embodiments of the present application can achieve the following technical effects: 1) through the analysis of the account behavior by the virtual digital person, the corresponding level information, title, display, etc. are given, which can combine the virtual digital person with the real employee's growth experience, and make the two produce emotional interaction and collaborative growth. The level information obtained by the account can be fed back to the system to revise the corresponding account experience behavior. 2) supplement the missing account experience behavior of the virtual digital person in the existing office system.

[0086] The embodiments of the present application also provide an account evaluation device. It should be noted that the account evaluation device of the embodiments of the present application can be used to execute the account evaluation method provided by the embodiments of the present application. The account evaluation device provided by the embodiments of the present application is introduced as follows.

[0087] Figure 7 is a schematic diagram of the account evaluation device according to the embodiments of the present application. As shown in Figure 7 the device includes a first acquisition module 702, a first determination module 704, a first judgment module 706, and a second determination module 708.

[0088] The first acquisition module 702 is configured to acquire operation behavior data of a target account in N terminals, where N is an integer greater than or equal to 2.

[0089] The first determination module 704 is connected to the first acquisition module 702 and is configured to determine a first parameter value based on the operation behavior data of the target account in the N terminals, where the first parameter value is used to indicate the similarity between the operation behaviors of the target account in the N terminals.

[0090] The first determining module 704 is connected to the first obtaining module 702, and is configured to determine a first parameter value based on the operation behavior data of the target account on the N terminals.

[0091] The second determining module 708 is connected to the first judging module 706, and is configured to determine an evaluation result of the target account based on the operation behavior data of the target account on the N terminals, if the first parameter value is in the preset first numerical interval.

[0092] In the present application, the first obtaining module 702 is configured to obtain operation behavior data of a target account on N terminals, where N is an integer greater than or equal to 2. The first determining module 704 is configured to determine a first parameter value based on the operation behavior data of the target account on the N terminals, where the first parameter value is used to indicate the similarity between the operation behaviors of the target account on the N terminals. The first judging module 706 is configured to determine whether the first parameter value is in a preset first numerical interval. The second determining module 708 is configured to determine an evaluation result of the target account based on the operation behavior data of the target account on the N terminals, if the first parameter value is in the preset first numerical interval. The purpose of accurately evaluating the account behavior by comprehensively considering the operation behavior data of multiple terminals is achieved, thereby realizing the technical effect of improving the accuracy and applicability of account evaluation, and further solving the technical problems of low accuracy and poor applicability of the account evaluation method based on a single terminal in the related art.

[0093] It should be noted that each of the above modules can be implemented by software or hardware. For example, for the latter, the modules can be located in the same processor, or in different processors in any combination.

[0094] It should be noted that the first obtaining module 702, the first determining module 704, the first judging module 706, and the second determining module 708 correspond to steps S102 to S108 in the embodiments, and have the same instances and application scenarios as the corresponding steps, but are not limited to the disclosed contents in the above embodiments. It should be noted that the modules as part of the device can run in a computer terminal.

[0095] It should be noted that the optional or preferred embodiments of the present embodiment can refer to the related descriptions in the embodiments, which will not be repeated here.

[0096] The aforementioned account evaluation device may further include a processor and a memory. The first acquisition module 702, the first determination module 704, the first judgment module 706, the second determination module 708, etc., are all stored in the memory as program modules, and the processor executes the aforementioned program modules stored in the memory to realize the corresponding functions.

[0097] The processor contains a kernel, which retrieves the corresponding program units from memory. One or more kernels can be configured, and their parameters can be adjusted (for the purposes of this application).

[0098] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0099] This application provides a non-volatile storage medium storing a program that, when executed by a processor, implements the aforementioned account evaluation method.

[0100] This application provides a processor for running a program, wherein the program executes the account evaluation method described above.

[0101] like Figure 8 As shown, this application provides an electronic device 10, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps: acquiring operational behavior data of a target account on N terminals, where N is an integer greater than or equal to 2; determining a first parameter value based on the operational behavior data of the target account on the N terminals, wherein the first parameter value indicates the degree of similarity between the operational behaviors of the target account on the N terminals; determining whether the first parameter value is within a preset first value range; and if the first parameter value is within the preset first value range, determining an evaluation result for the target account based on the operational behavior data of the target account on the N terminals. The device in this document can be a server, PC, PAD, mobile phone, etc.

[0102] The application further provides a computer program product, which is adapted to execute a program for initializing the following method steps when executed on a data processing device: obtaining operation behavior data of a target account on N terminals respectively, wherein N is an integer greater than or equal to 2; determining a first parameter value based on the operation behavior data of the target account on the N terminals respectively, wherein the first parameter value is used to indicate a similarity degree between the operation behaviors of the target account on the N terminals respectively; judging whether the first parameter value is in a preset first numerical interval; and if the first parameter value is in the preset first numerical interval, determining an evaluation result of the target account based on the operation behavior data of the target account on the N terminals respectively.

[0103] Optionally, the computer program product is further adapted to execute a program for initializing the following method steps: if the first parameter value is in a preset second numerical interval, determining a first terminal from the N terminals, wherein a similarity between the operation behavior data of the target account on the first terminal and the operation behavior data of the target account on other terminals is less than a preset similarity threshold, wherein the other terminals are terminals other than the first terminal in the N terminals, and a lower limit value of the preset first numerical interval is greater than or equal to a lower limit value of the preset second numerical interval; determining a second parameter value corresponding to the first terminal based on operation behavior data of M accounts corresponding to the first terminal, wherein the second parameter value is used to indicate a similarity degree between the operation behaviors of the accounts included in the first terminal, and M is an integer greater than or equal to 2; judging whether the second parameter value is in a preset third numerical interval; and if the second parameter value is in the preset third numerical interval, determining new operation behavior data of the target account on the first terminal based on the operation behavior data of the M accounts corresponding to the first terminal; and determining the evaluation result of the target account based on the operation behavior data of the target account on the other terminals and the new operation behavior data of the target account on the first terminal.

[0104] Optionally, the computer program product is further adapted to execute a program for initializing the following method steps: if the second parameter value is in a preset fourth numerical interval, determining preset operation behavior data as the new operation behavior data of the target account on the first terminal, wherein a lower limit value of the preset third numerical interval is greater than or equal to an upper limit value of the preset fourth numerical interval; and determining the evaluation result of the target account based on the operation behavior data of the target account on the other terminals and the new operation behavior data of the target account on the first terminal.

[0105] Optionally, the computer program product is further adapted to execute a program which is initialized with the following method steps: calculating an average value of the operation behavior data of the M accounts corresponding to the first terminal; and determining the new operation behavior data of the target account at the first terminal according to the average value.

[0106] Optionally, the computer program product is further adapted to execute a program which is initialized with the following method steps: determining a comprehensive operation behavior score of the target account based on the operation behavior data of the target account at the N terminals respectively; and determining the evaluation result of the target account based on the comprehensive operation behavior score.

[0107] Optionally, the computer program product is further adapted to execute a program which is initialized with the following method steps: determining a comprehensive operation behavior score of the target account based on the operation behavior data of the target account at the N terminals respectively; and determining the evaluation result of the target account based on the comprehensive operation behavior score.

[0108] Optionally, the computer program product is further adapted to execute a program which is initialized with the following method steps: obtaining a preset database, wherein the preset database stores a plurality of operation behavior score intervals and a behavior level corresponding to each of the plurality of operation behavior score intervals; determining a target operation behavior score interval to which the comprehensive operation behavior score belongs; determining a target behavior level corresponding to the target operation behavior score interval from the preset database; and determining the evaluation result of the target account according to the target behavior level.

[0109] Those skilled in the art understand that embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can be in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0110] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the computer or other programmable data processing apparatus produce a device that implements the functions specified in the flowcharts and / or block diagrams. These computer program instructions can also be stored in a computer-usable storage medium that can guide a computer or other programmable data processing apparatus to work in a specific manner, so that the computer or other programmable data processing apparatus produces a device that implements the functions specified in the flowcharts and / or block diagrams.Figure 1 one or more processes and / or blocks Figure 1 means for performing the function specified by the block or blocks.

[0111] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the Figure 1 one or more processes and / or blocks Figure 1 means for performing the function specified by the block or blocks.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the Figure 1 one or more processes and / or blocks Figure 1 Figure 1 means for performing the function specified by the block or blocks.

[0113] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0114] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or cache memory. The memory can also include non-volatile memory, such as read-only memory (ROM), electrically programmable read-only memory (EPROM), electrically erasable read-only memory (EEPROM), programmable read-only memory (PROM), flash memory, or any other non-volatile memory. Memory is an example of computer-readable media.

[0115] Computer-readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile discs (DVDs) or other optical storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer-readable media does not include transitory media, such as modulated data signals and carrier waves.

[0116] It is also to be noted that the terms "comprising", "including", and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises a... " does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0117] Those skilled in the art will appreciate that embodiments of the present application can be devised for a method, a system, or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer-readable program code.

[0118] The embodiments of the present application are only illustrative and are not intended to limit the present application. Various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. An account evaluation method characterized by, The method comprises: obtaining operation behavior data of a target account on N terminals respectively, wherein N is an integer greater than or equal to 2; determining a first parameter value based on the operation behavior data of the target account on the N terminals respectively, wherein the first parameter value is used to indicate a similarity between operation behaviors of the target account on the N terminals respectively; judging whether the first parameter value is in a preset first numerical interval; if the first parameter value is in the preset first numerical interval, determining an evaluation result of the target account based on the operation behavior data of the target account on the N terminals respectively; wherein the method further comprises: if the first parameter value is in a preset second numerical interval, determining a first terminal from the N terminals, wherein a similarity between operation behavior data of the target account on the first terminal and operation behavior data of the target account on other terminals is less than a preset similarity threshold, wherein the other terminals are terminals other than the first terminal among the N terminals, a lower limit value of the preset first numerical interval is greater than or equal to a lower limit value of the preset second numerical interval; determining a second parameter value corresponding to the first terminal based on operation behavior data of M accounts corresponding to the first terminal, wherein the second parameter value is used to indicate a similarity between operation behaviors of accounts included in the first terminal, and M is an integer greater than or equal to 2; judging whether the second parameter value is in a preset third numerical interval; if the second parameter value is in the preset third numerical interval, determining new operation behavior data of the target account on the first terminal based on the operation behavior data of the M accounts corresponding to the first terminal; determining the evaluation result of the target account based on the operation behavior data of the target account on the other terminals and the new operation behavior data of the target account on the first terminal.

2. The method of claim 1, wherein, The method further comprises: if the second parameter value is in a preset fourth numerical interval, determining preset operation behavior data as the new operation behavior data of the target account on the first terminal, wherein a lower limit value of the preset third numerical interval is greater than or equal to an upper limit value of the preset fourth numerical interval; determining the evaluation result of the target account based on the operation behavior data of the target account on the other terminals and the new operation behavior data of the target account on the first terminal.

3. The method of claim 1, wherein, The determination of the new operation behavior data of the target account on the first terminal based on the operation behavior data of the M accounts corresponding to the first terminal comprises: calculating an average value of the operation behavior data of the M accounts corresponding to the first terminal; determining the new operation behavior data of the target account on the first terminal according to the average value.

4. The method according to any one of claims 1 to 3, characterized in that, The determination of the evaluation result of the target account based on the operation behavior data of the target account on the N terminals respectively comprises: determining a comprehensive operation behavior score of the target account based on the operation behavior data of the target account on the N terminals respectively; Determine the evaluation result of the target account based on the comprehensive operation behavior score.

5. The method of claim 4, wherein, The determination of the comprehensive operation behavior score of the target account based on the operation behavior data of the target account at the N terminals respectively comprises: Based on the operation behavior data of the target account at the N terminals respectively; Determine the weight value corresponding to each of the N terminals; Based on the operation behavior data of the target account at the N terminals respectively and the weight value corresponding to each of the N terminals, obtain the comprehensive operation behavior score.

6. The method of claim 4, wherein, The determination of the evaluation result of the target account based on the comprehensive operation behavior score comprises: Obtain a preset database, wherein the preset database stores a plurality of operation behavior score intervals and the behavior level corresponding to each of the plurality of operation behavior score intervals; Determine the target operation behavior score interval to which the comprehensive operation behavior score belongs; Determine the target behavior level corresponding to the target operation behavior score interval from the preset database; Determine the evaluation result of the target account according to the target behavior level.

7. An account evaluation apparatus characterized by comprising: Comprise: The first acquisition module is used for acquiring the operation behavior data of the target account at the N terminals respectively, wherein N is an integer greater than or equal to 2; The first determination module is used for determining the first parameter value based on the operation behavior data of the target account at the N terminals respectively, wherein the first parameter value is used to indicate the similarity between the operation behaviors of the target account at the N terminals respectively; The first judgment module is used for judging whether the first parameter value is in a preset first value interval; The second determination module is used for determining the evaluation result of the target account based on the operation behavior data of the target account at the N terminals respectively if the first parameter value is in the preset first value interval; The device is further configured to: if the first parameter value is in a preset second numerical interval, determine a first terminal from the N terminals, wherein a similarity between the operation behavior data of the target account in the first terminal and the operation behavior data of the target account in other terminals is less than a preset similarity threshold, the other terminals being terminals other than the first terminal among the N terminals, and a lower limit value of the preset first numerical interval being greater than or equal to a lower limit value of the preset second numerical interval; determine a second parameter value corresponding to the first terminal based on the operation behavior data of the M accounts corresponding to the first terminal, wherein the second parameter value is used to indicate a similarity degree between the operation behaviors of the accounts included in the first terminal, M being an integer greater than or equal to 2; determine whether the second parameter value is in a preset third numerical interval; if the second parameter value is in the preset third numerical interval, determine new operation behavior data of the target account in the first terminal based on the operation behavior data of the M accounts corresponding to the first terminal; and determine the evaluation result of the target account based on the operation behavior data of the target account in the other terminals and the new operation behavior data of the target account in the first terminal.

8. A non-volatile storage medium, comprising: The non-volatile storage medium stores a plurality of instructions, the instructions being adapted to be loaded and executed by a processor to implement the account evaluation method in any one of claims 1 to 6.

9. An electronic device, comprising: The device comprises one or more processors and a memory, and the memory is configured to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the account evaluation method in any one of claims 1 to 6.

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