A task sheet processing method and system

Abstract

The present invention provides a method and system for processing task sheets. The method includes obtaining historical access data of historical users, where each piece of historical access data includes an exposed task sheet and click data for each exposed task sheet; determining a vector set of the historical access data, and vectors in the vector set include personnel parameter values, task sheet parameter values, and click parameter values, wherein the click parameter values are determined based on the click data; determining a first model based on the vector set; obtaining user access information of a target user, where the user access information includes user identity information corresponding to the target user; determining a second model corresponding to the target user based on the user access information and the first model; and determining a recommended task sheet corresponding to the target user based on the second model. The present invention can be targeted at the preferences of user groups and / or individual users, making the presentation and / or recommendation of task sheets for each user more accurate and personalized, thereby improving user work efficiency.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and particularly to a task sheet processing method and system. Background Art

[0002] In engineering projects, task assignment and dispatch are usually involved. Task-related personnel (such as task dispatchers, task receivers, etc.) often need to view the task sheets in the task sheet list and perform corresponding operations on the task sheets. However, there are often many tasks in engineering projects, and the division of labor among personnel at all levels or positions is also relatively detailed. After the source tasks are dispatched layer by layer, a large number of task sheets will be formed. There may also be many task sheets in the task sheet list of task-related personnel. How to quickly find the target task sheet is of great significance for task execution. At the same time, different personnel focus on different tasks or task sheets, and the actual situation of the tasks (such as whether urgent processing, rectification is required, whether it is overdue, etc.) is also different. Manually sorting the task sheets by users is inefficient, and sorting the task sheets according to fixed task sheet information (such as task start time, task sheet status, etc.) lacks flexibility and is difficult to meet the actual needs. Therefore, how to present (such as sort) and / or recommend task sheets is an urgent problem to be solved.

[0003] Therefore, a task sheet processing method and system are provided, which can flexibly sort the task list in combination with the characteristics of personnel, the characteristics of task sheets and their actual situations, so that the presentation and / or recommendation of task sheets are more personalized and targeted. Summary of the Invention

[0004] The present invention provides a task sheet processing method, including: obtaining historical access data of historical users, each of the historical access data including an exposed task sheet and click data of each of the exposed task sheets; determining a vector set of the historical access data, vectors in the vector set including personnel parameter values, task sheet parameter values and click parameter values, wherein the click parameter values are determined based on the click data; determining a first model based on the vector set; obtaining user access information of a target user, the user access information including user identity information corresponding to the target user; determining a second model corresponding to the target user based on the user access information and the first model; and determining a recommended task sheet corresponding to the target user based on the second model.

[0005] The present invention provides a task order processing system, including: a first acquisition module configured to acquire historical access data of historical users, each of the historical access data including exposure task orders and click data of each exposure task order; a vector set determination module configured to determine a vector set of the historical access data, vectors in the vector set including personnel parameter values, task order parameter values, and click parameter values, wherein the click parameter values are determined based on the click data; a first model determination module configured to determine a first model based on the vector set; a second acquisition module configured to acquire user access information of a target user, the user access information including user identity information corresponding to the target user; a second model determination module configured to determine a second model corresponding to the target user based on the user access information and the first model; and a recommendation module configured to determine a recommended task order corresponding to the target user based on the second model.

[0006] The beneficial effects that the present invention may bring include but are not limited to: (1) Through a large amount of historical access data corresponding to a large number of historical users, a first model that conforms to the preferences of most people can be obtained to quickly comprehensively sort the task orders of any individual; (2) Based on the first model, combined with the information of the target individual, a second model is generated, making the sequence of the automatically generated task order list more personalized and accurate; (3) Regularly update the first model and / or the second model, so that the updated first model and / or the second model can adapt to the access situation of task order information and the changes in different user information in the actual application scenario, thereby making the sorting of task orders more in line with the actual needs; (4) Through the design of effective parameter value combinations and their influencing factors, the influencing factors that trigger users to click on the task order in the task order can be analyzed more accurately, so that the sorting of the task order by the first model and / or the second model is more accurate, thus meeting the needs of users. Brief Description of the Drawings

[0007] The present invention will be further described in the form of exemplary embodiments, and these exemplary embodiments will be described in detail through the drawings. These embodiments are not restrictive. In these embodiments, the same numbers represent the same structures, wherein:

[0008] Figure 1 is a schematic diagram of an application scenario of a task order processing system according to some embodiments of the present invention;

[0009] Figure 2 is a schematic diagram of modules of a task order processing system according to some embodiments of the present invention;

[0010] Figure 3 is an exemplary flowchart of a task order processing method according to some embodiments of the present invention;

[0011] Figure 4a is an exemplary flowchart of a method for determining a first model according to some embodiments of the present invention;

[0012] Figure 4b is a schematic diagram of a process for determining a first model according to some embodiments of the present invention;

[0013] Figure 5a is a schematic diagram of a process for determining a second model according to some embodiments of the present invention;

[0014] Figure 5b is a schematic diagram of a process for updating a second model according to some embodiments of the present invention;

[0015] Figure 6 is a schematic diagram of a process for determining a recommended task list according to some embodiments of the present invention. Detailed implementation manners

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings used in the description of the embodiments. Obviously, the accompanying drawings in the following description are only some examples or embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, the present invention can also be applied to other similar scenarios based on these drawings. Unless obvious from the language context or otherwise stated, the same reference numerals in the drawings represent the same structure or operation.

[0017] It should be understood that the "system", "device", "unit" and / or "module" used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the said words can be replaced by other expressions.

[0018] Unless the context clearly indicates an exception, the words "a", "an", "one" and / or "the" etc. do not specifically refer to the singular, but may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0019] Flowcharts are used in the present invention to illustrate the operations performed by the systems according to the embodiments of the present invention. It should be understood that the operations before or after do not necessarily need to be executed precisely in sequence. On the contrary, they can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several operations can be removed from these processes.

[0020] Figure 1It is a schematic diagram of the application scenario of a task order processing system shown in some embodiments of the present invention.

[0021] As Figure 1 shown, the application scenario 100 of the task order processing system includes a processing device 110, a network 120, a terminal 130, a storage device 140, and a task information database 150.

[0022] The processing device 110 can process data and / or information obtained from the terminal 130, the storage device 140, and the task information database 150. For example, the processing device 110 can obtain task-related information from the task information database 150 and generate a task order list based on the task-related information. As another example, the processing device 110 can generate a first model and / or a second model corresponding to the target user based on the task-related information for sorting the task order list. More content about the first model and the second model can be found elsewhere in the present invention (for example, Figure 3 )

[0023] In some embodiments, the processing device 110 can be a single server or a server group. In some embodiments, the processing device 110 can be local or remote. The processing device 110 can be directly connected to the terminal 130, the storage device 140, and the task information database 150 to access the stored or obtained information and / or data. In some embodiments, the processing device 110 can be implemented on a cloud platform. By way of example only, the cloud platform can include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, etc. or any combination thereof. In some embodiments, the processing device 110 can be a distributed server group, which can include multiple server nodes.

[0024] The network 120 can include any suitable network that facilitates the exchange of information and / or data in the application scenario 100 of the task order processing system. In some embodiments, one or more components of the application scenario 100 of the task order processing system (e.g., the terminal 130, the processing device 110, the storage device 140, or the task information database 150) can transmit information and / or data to one or more other components of the application scenario 100 of the task order processing system via the network 120. For example, the processing device 110 can obtain task-related information from the storage device 140 and / or the task information database 150 via the network 120.

[0025] In some embodiments, the network 120 can be any one or more of a wired network or a wireless network. In some embodiments, the network can be various topological structures such as point-to-point, shared, centralized, etc. or a combination of multiple topological structures.

[0026] The terminal 130 may include a mobile device 130-1, a tablet computer 130-2, a laptop computer 130-3, etc., or any combination thereof. In some embodiments, the terminal 130 may interact with other components in the application scenario 100 of the work order processing system via the network 120. In some embodiments, the terminal 130 may receive information and / or instructions input by a user, and send the received information and / or instructions to the processing device 110 via the network 120. For example, the terminal 130 may receive instructions from a user (such as a dispatcher or an acceptor), obtain task-related information from the storage device 140 and / or the task information database 150 via the network 120, and present one or more work orders in the form of a list.

[0027] In some embodiments, the application scenario 100 of the work order processing system further includes a preset client application, which may be software or an application installed on the terminal 130. For example, it may be a mobile application installed on the mobile device 130-1, a desktop application installed on the laptop computer 130-3, etc. In some embodiments, the client application includes a visual user interface to present task-related information to the user. For example, the user interface presents a task list, which contains multiple work orders processed based on a sorting algorithm. Among them, the sorting algorithm may be preset / default or specified by the user. In some embodiments, the sorting algorithm may also be implemented based on a first model or a second model.

[0028] In some embodiments, the client application may also interact with the user (such as a dispatcher, an acceptor, etc.) through the user interface. For example, the client application may respond to the user's operations on the work orders presented on the user interface and generate corresponding operation event records. Exemplarily, it may respond to the user's click event on the work order (such as a mouse click / double-click event, a gesture click event, etc.) and generate a click event record. The click event record includes, but is not limited to, the operator id, the work order id of the clicked work order, the click time, the number of clicks, etc. In some embodiments, the client application may send the operation event record (such as the click event record) to the storage device 140 and / or the task information database 150 via the network 120 for storage. In some embodiments, the operation event record may be generated by the processing device 110.

[0029] In some embodiments, the processing device 110 may perform deduplication processing on click event records. For example, the processing device 110 may obtain multiple click event records from the task information database 150 and perform deduplication processing based on the operator id, work order id, click time, and a preset deduplication time threshold in the multiple click event records. Exemplarily, in response to the operator id and work order id in the multiple click event records being the same and the difference between the multiple click times being within the deduplication time threshold (such as 2 s), the processing device 110 stores only one of the click event records (such as the click event record with the earliest click time).

[0030] In some embodiments, the client application may perform deduplication processing on click events based on the deduplication time threshold (such as 2 seconds). For example, when the user clicks multiple times (such as 3 times) within the deduplication time threshold, the client application only sends the click event record corresponding to the first click event to the storage device 140 for storage. By performing deduplication processing on click events in the client application, data transmission can be reduced, and at the same time, the data processing pressure on the processing device 110 can be reduced.

[0031] The storage device 140 may store data and / or instructions. In some embodiments, the storage device 140 may store data obtained from the processing device 110, the terminal 130, and / or the task information database 150. For example, the storage device 140 may store data (such as task-related information) obtained from the task information database 150. In some embodiments, the storage device 140 may store data and / or instructions for the processing device 110 to execute the exemplary methods described in the present invention. For example, the storage device 140 may store instructions for the processing device 110 to execute the methods shown in the respective flowcharts. In some embodiments, the storage device 140 may include a mass storage device, a removable storage device, a volatile read-write memory, a read-only memory (ROM), etc., or any combination thereof. In some embodiments, the storage device 140 may be implemented on a cloud platform. In some embodiments, the storage device 140 may be a part of the processing device 110.

[0032] The task information database 150 refers to a source for providing data related to tasks. For example, it can be a database of an operating entity (such as an enterprise, a construction unit, etc.) and / or a third-party service platform (such as an information service provider). In some embodiments, the task information database 150 can be used to provide various types of task-related information. For example, the task-related information includes the values of task order parameters (such as task ID, creation time, dispatch time, acceptance time, associated subtasks, task execution status, etc.), the values of personnel parameters (such as the IDs, names, positions, etc. of the dispatcher, acceptor, person in charge, executor, etc.). For another example, the task-related information can include the historical access information of the task order (such as the number of times it has been queried or clicked). It should be noted that the task-related information can include various forms of information such as text, graphics, sound, video, etc.

[0033] In some embodiments, the task information database 150 can interact with other components in the application scenario 100 of the task order processing system through the network 120. For example, it can send task-related information (such as task order information, personnel information, etc.) to the processing device 110 through the network 120, so that the processing device 110 can perform the analysis and / or processing of the task order. For another example, the task information database 150 can send task-related information to the terminal 130 through the network 120, so that the terminal 130 can present the task-related information to the user. In some embodiments, the task information database 150 can be integrated or deployed in the storage device 140.

[0034] The above description is only for illustrative purposes, and actual application scenarios can vary in various ways.

[0035] It should be noted that the application scenario 100 of the task order processing system is only provided for illustrative purposes and is not intended to limit the scope of the present invention. For those of ordinary skill in the art, various modifications or changes can be made according to the description of the present invention. However, these changes and modifications will not deviate from the scope of the present invention.

[0036] Figure 2 is a schematic diagram of the modules of the task order processing system according to some embodiments of the present invention.

[0037] As Figure 2 shown, the task order processing system 200 can include a first acquisition module 210, a vector set determination module 220, a first model determination module 230, a second acquisition module 240, a second model determination module 250, and a recommendation module 260.

[0038] The first acquisition module 210 is configured to acquire the historical access data of historical users, and each historical access data includes an exposed task order and the click data of each exposed task order.

[0039] The vector set determination module 220 is configured to determine a vector set of historical access data. The vectors in the vector set include personnel parameter values, work order parameter values, and click parameter values, where the click parameter values are determined based on click data.

[0040] In some embodiments, the vector set includes vectors corresponding to each exposure work order of each historical access data. The vector set determination module 220 is further configured to: for each exposure work order of each historical access data, determine a work order sub-vector based on the work order parameter value of the exposure work order; determine a personnel sub-vector based on the personnel parameter value of the exposure work order; determine a click sub-vector based on the click parameter value of the exposure work order; and determine the vector corresponding to the exposure work order based on the work order sub-vector, the personnel sub-vector, and the click sub-vector.

[0041] The first model determination module 230 is configured to determine a first model based on the vector set.

[0042] The first model reflects the influence degree of work order-related parameter values on the click events of the historical user.

[0043] In some embodiments, the first model determination module 230 is further configured to: determine a plurality of effective parameters based on the vectors in the vector set; determine a plurality of combinations of effective parameter values based on the plurality of effective parameters, where each combination of effective parameter values includes at least one personnel parameter value and at least one work order parameter value; determine the influence factor of each combination of effective parameter values based on the vectors in the vector set; and determine the first model based on each combination of effective parameter values and its influence factor.

[0044] In some embodiments, the first model determination module 230 is further configured to: determine the occurrence frequency of each parameter based on the vectors in the vector set; and determine a plurality of effective parameters based on the occurrence frequency of each parameter and a preset frequency threshold.

[0045] In some embodiments, the first model determination module 230 is further configured to: for each vector in the vector set, determine an effective vector based on the plurality of effective parameters and their corresponding activation ranges; and determine at least one combination of effective parameter values based on the effective vectors, where the plurality of combinations of effective parameter values includes at least one combination of effective parameter values corresponding to each vector.

[0046] In some embodiments, the first model determination module 230 is further configured to: determine the influence factor based on the occurrence times and / or click times of each combination of effective parameter values.

[0047] The second acquisition module 240 is configured to acquire the user access information of the target user, where the user access information includes the user identity information corresponding to the target user.

[0048] The second model determination module 250 is configured to determine a second model corresponding to a target user based on user access information and a first model.

[0049] The second model reflects the influence degree of task order related parameter values on the click event of the target user.

[0050] In some embodiments, the second model determination module 250 is further configured to: determine a dedicated parameter value combination corresponding to the target user and its influence factor based on the user identity information corresponding to the target user and the personnel parameter value in each valid parameter value combination in the first model; determine the second model based on the dedicated parameter value combination and its influence factor.

[0051] In some embodiments, the second model determination module 250 is further configured to: obtain a target exposure task order corresponding to the target user and target click data of the target user on the target exposure task order; update the second model based on the target exposure task order and the target click data.

[0052] In some embodiments, the second model determination module 250 is further configured to: obtain identity change information of the target user; determine an updated dedicated parameter value combination corresponding to the target user and its influence factor based on the identity change information; update the second model corresponding to the target user based on the updated dedicated parameter value combination and its influence factor.

[0053] The recommendation module 260 is configured to determine a recommended task order corresponding to the target user based on the second model.

[0054] In some embodiments, the recommendation module 260 is further configured to: determine a target task order parameter value corresponding to each target task order based on the target task order information corresponding to the target task order related to the target user; determine a plurality of target parameter value combinations corresponding to each target task order based on the target task order parameter value and the target personnel parameter value of the target user; determine a recommendation weight corresponding to each target task order based on the plurality of target parameter value combinations and the second model; determine the recommended task order based on the recommendation weight.

[0055] In some embodiments, the first model determination module 230 is further configured to group the vector set to obtain a plurality of vector groups; determine the first model based on each vector group to obtain a plurality of first models; and the second model determination module 250 is further configured to select a target first model corresponding to the target user from the plurality of first models; determine the second model based on the target first model and user access information.

[0056] It should be noted that the above description of the task sheet processing system 200 and its modules is only for convenience of description and does not limit the present invention to the scope of the illustrated embodiments. It can be understood that for those skilled in the art, after understanding the principle of the system, various modules may be arbitrarily combined without departing from this principle, or a subsystem may be formed and connected to other modules. For example, the first acquisition module 210, the vector set determination module 220, the first model determination module 230, the second acquisition module 240, the second model determination module 250, and the recommendation module 260 may be different modules in the system, or a single module may implement the functions of two or more of the above modules. For example, each module may share a storage module, or each module may have its own storage module separately. Such variations are all within the protection scope of the present invention.

[0057] Figure 3 is an exemplary flowchart of a task sheet processing method according to some embodiments of the present invention.

[0058] In some embodiments, process 300 may be executed by a task sheet processing system. As Figure 3 shown, process 300 includes the following steps.

[0059] Step S310, obtaining historical access data of historical users, where each historical access data includes an exposed task sheet and click data for each exposed task sheet.

[0060] A historical user refers to a user who has accessed task sheet data through a client application. For example, when a historical user inputs a query or retrieval instruction through a client application, the client application may present a corresponding task sheet list for the historical user to access. A user refers to a person related to a task, which may be any person in an operating entity (such as an enterprise or a construction unit). A user may include a task assigner, a task receiver, a supervisor, a person in charge, an executor, etc. Among them, a task refers to a matter that needs to be executed or processed by a user, which may be represented in the form of a task document (i.e., a task sheet). A task sheet may include a combination of one or more of various task-related information. For more content about task-related information, see Figure 1 and its description.

[0061] Historical access data refers to the access event records of historical users to task sheet data in the past period of time, including various information related to the access event. For example, the past period of time may be within the past month, three months, half a year, etc. Information related to the access event includes the access time, access content, and the interaction behavior (such as clicking) between the historical user and the access content.

[0062] An exposure task list refers to a task list that has been presented to historical users for browsing. For example, it can be one or more task lists presented within the view of historical users on the interface of a client application. Exemplarily, when a historical user inputs a query or retrieval instruction through the client application, the corresponding task list can be presented for the historical user to access. When there are a large number of task lists in the task list, the task lists need to be displayed in pages. For the multiple task lists displayed in pages, the multiple task lists on the current page and the browsed pages are exposure task lists, and the task lists that have not been paged and browsed by historical users belong to unexposed task lists.

[0063] In some embodiments, the processing device 110 can mark the exposure status of the task list through the client application (such as 1 indicating exposed and 0 indicating unexposed) to determine the set of exposure task lists corresponding to each historical user.

[0064] The click data of the exposure task list is related to the click events of historical users on the exposure task list, and it includes the click parameter values of the click parameters. The click parameters include click time, click count, the id of the historical person who executed the click event, the id of the exposed task list that was clicked, etc. In some embodiments, the click data of the exposure task list contains the click event records after duplicate removal processing. Exemplarily, if the historical person id and the exposed task list id in multiple click event records are the same, and the difference between multiple click times is within the duplicate removal time threshold (such as 2s), then only one click event record will be retained from these multiple click event records. Correspondingly, the corresponding multiple click events will be recorded as one click event.

[0065] In some embodiments, the historical access data further includes other relevant data of the exposure task list, such as personnel data (such as personnel parameter values) and task list data (such as task list parameters). For more content about personnel parameters and task list parameters, reference can be made to the description of step S320.

[0066] Step S320: Determine the vector set of the historical access data. The vectors in the vector set include personnel parameter values, task list parameter values, and click parameter values.

[0067] The vector set of the historical access data refers to a set constructed by multiple vectors generated based on the historical access data, which can reflect the data characteristics of the historical access data. Each vector in the vector set includes the type or parameter of the data characteristics (such as name, department) and the corresponding characteristic value or parameter value of the data characteristics (such as "Xiaoqiang", "Administrative Department").

[0068] In some embodiments, the task sheet processing system may generate a vector corresponding to each historical access data (such as database records). Among them, the vector includes the values of multiple elements, each element represents a parameter, and the value of the element represents the specific parameter value. Exemplarily, the vector Vector is (101, Xiao Qiang, Administrative Department, Minister), where the parameters of the vector are personnel number, name, department, and position respectively, and the parameter values are 101, Xiao Qiang, Administrative Department, and Minister respectively.

[0069] It can be understood that different access data contains different information, and their corresponding vectors may be different. The task sheet processing system may generate a vector set based on multiple vectors corresponding to multiple historical access data.

[0070] In some embodiments, the vector set includes vectors corresponding to each exposure task sheet of each historical access data. For each exposure task sheet of each historical access data, the task sheet processing system may determine a task sub-vector based on the task sheet parameter value of the exposure task sheet; determine a personnel sub-vector based on the personnel parameter value of the exposure task sheet; determine a click sub-vector based on the click parameter value of the exposure task sheet; and determine the vector corresponding to the exposure task sheet based on the task sub-vector, personnel sub-vector, and click sub-vector. Hereinafter, the vector corresponding to the exposure task sheet is simply referred to as the exposure task sheet vector.

[0071] The task sheet parameter value refers to the value of the task sheet parameter of the exposure task sheet. Exemplary task sheet parameters include task ID, creation time, dispatch time, acceptance time, associated sub-tasks, task execution status, review status, task sheet hierarchy, etc. The task sheet processing system may determine the task sub-vector according to the task sheet parameter and its parameter value corresponding to each exposure task sheet. In some embodiments, the task sheet parameter value is determined based on the task sheet data in the historical access data obtained in step S310. In some embodiments, the task sheet processing system obtains the task sheet parameter value of the exposure task sheet by querying the task information database 150.

[0072] The personnel parameter value refers to the value of the personnel parameter of the exposure task sheet. Exemplary personnel parameters include the id, name, age, department, position, etc. of the task-related personnel such as the dispatcher, acceptor, person in charge, executor, etc. The task sheet processing system may determine the personnel sub-vector according to the personnel parameter and its parameter value corresponding to each exposure task sheet. In some embodiments, the task sheet parameter value is determined based on the personnel data in the historical access data obtained in step S310. In some embodiments, the task sheet processing system obtains the personnel parameter value of the exposure task sheet by querying the task information database 150.

[0073] The click parameter value refers to the value of the click parameter in the exposure task sheet. The task sheet processing system can determine the click sub-vector according to the click parameter and its parameter value of each exposure task sheet. The click parameter value can be determined based on the click data in the historical access data obtained in step S310.

[0074] It should be noted that the vector corresponding to the exposure task sheet may also include other parameter information. For example, the parameter values of the access parameters (such as query time, number of queries, etc.) of the relevant personnel for the exposure task sheet.

[0075] In some embodiments, the task sheet processing system can splice the task sheet sub-vector, the personnel sub-vector, and the click sub-vector to obtain the exposure task sheet vector. Exemplarily, the exposure task sheet vector V is (F task 、F member 、F tap ), where F task 、F member 、F tap represent the task sheet sub-vector, the personnel sub-vector, and the click sub-vector respectively.

[0076] It should be noted that information extraction can be performed on the exposure task sheet according to a preset rule to determine the exposure task sheet vector. In some embodiments, the task sheet processing system can determine the task sheet sub-vector, the personnel sub-vector, and the click sub-vector respectively according to the parameter weights of the parameters in the task sheet parameters, personnel parameters, and click parameters, and then determine the exposure task sheet vector.

[0077] Taking the personnel sub-vector as an example, the parameter weights of personnel parameters such as user ID, work number, and name can be set relatively large (such as greater than a threshold), and the parameter weights of personnel parameters such as age and address can be set relatively small (such as less than a threshold). The task sheet processing system can generate the personnel sub-vector according to the personnel parameters with parameter weights greater than the threshold.

[0078] In some embodiments of the present invention, by setting the parameter weights of the parameters in the task sheet parameters, personnel parameters, and click parameters to determine the exposure task sheet vector, some irrelevant parameters can be excluded according to actual needs, thereby reducing the subsequent data processing volume.

[0079] Step S330, determine the first model based on the vector set.

[0080] The first model refers to a general task sheet sorting model generated based on the historical access data (or vector set) of multiple historical users.

[0081] The first model can reflect the first degree of influence of task order related parameter values (such as personnel parameters, task order parameters) on the click events of historical users, and thus can be used for task order sorting. For example, the first degree of influence can be represented by a value in the interval [0, 1], and the larger the value, the more likely the task order related parameter value is to trigger historical users to click on the exposed task order. In an actual scenario (such as accessing a task order through an application), if the first degree of influence corresponding to the value of the task order parameter of a certain task order is large, then this task order can be placed in a higher position in the task order list for the user to view or click.

[0082] In some embodiments, the task order processing system can analyze the historical access data of multiple historical users to generate the first model. For example, for multiple exposed task orders in the historical access data, the task order processing system can count the occurrence frequencies of different task order parameter values or combinations, as well as the number of clicks on the exposed task orders corresponding to the task order parameter values or combinations. The more the number of clicks, the greater the first degree of influence corresponding to the task order parameter value or combination. Further, the first model can sort the multiple exposed task orders according to the first degree of influence corresponding to different task order parameter values or combinations and the task order parameters in the multiple exposed task orders.

[0083] In some embodiments, the task order processing system can process the vector set to determine the first model. For more content about the first model, see Figure 4a its description.

[0084] In some embodiments, multiple historical users can be divided into multiple different user groups, and the task order processing system can generate multiple different first models for the multiple different user groups. Among them, the user groups can be determined according to actual needs. For example, the user groups can include, but are not limited to, multiple different user groups divided by department, gender, position, type of work, etc. As an example, the first model can include the first model for construction workers, the first model for administrative department personnel, etc.

[0085] In some embodiments, the task order processing system can group the vector set to obtain multiple vector groups; and determine the first model based on each vector group to obtain multiple first models. For more relevant content, see Figure 4a its description.

[0086] Step S340, obtain the user access information of the target user, where the user access information includes the user identity information corresponding to the target user.

[0087] The target user refers to an individual user who has a need to access task list data. For example, the target user can be a user in the administrative department. The user identity information corresponding to the target user includes but is not limited to work number, name, position, etc. In some embodiments, the user identity information also includes the user's login information (such as user ID, account, etc.).

[0088] Step S350, based on the user access information and the first model, determine the second model corresponding to the target user.

[0089] The second model refers to a task list sorting model for the target user, which can be called a dedicated sorting model. The second model can reflect the second influence degree of task list related parameter values (such as personnel parameters, task list parameters) on the click event of the target user. For example, the second influence degree can be represented by a numerical value in the interval [0,1], and the larger the value, the more likely the task list related parameter values are to trigger the target user to click on the exposed task list. In an actual scenario, if the second influence degree corresponding to the value of the task list parameter of a certain task list is larger, then this task list can be placed in a higher position in the task list for the target user to view or click.

[0090] In some embodiments, the task list processing system can determine the second model corresponding to the target user according to the identity information of the target user and the first model.

[0091] In some embodiments, the task list processing system can select the target first model corresponding to the target user from multiple first models; based on the target first model and the user access information, determine the second model. For more content about the second model, see Figure 5a and its description.

[0092] Step S360, based on the second model, determine the recommended task list corresponding to the target user.

[0093] The recommended task list refers to a task list that the target user may be concerned about or interested in, which may trigger a click event of the target user.

[0094] In some embodiments, the task list processing system can determine the recommended weights of multiple target tasks related to the target user based on the second model, and based on the recommended weights, determine the recommended task list. For more content about the recommended task list, see Figure 6 and its description.

[0095] In some embodiments, the task list processing system can present the recommended task list corresponding to the target user through the user interface of the client application, and can also remind the target user by means of text, voice, highlighting, etc.

[0096] In some embodiments, the task order processing system may update the first model according to a preset update period. The preset update period may be monthly, quarterly, etc. In some embodiments, the task order processing system may obtain the extended historical access data of historical users within the preset update period, determine an extended vector set based on the extended historical access data, and then determine to update the first model based on the current vector set and the extended vector set.

[0097] Among them, the extended historical access data refers to the historical access data of newly added historical users within the preset update period. Exemplarily, at the beginning of each month, the task order processing system may obtain the historical access data of historical users in the previous month as the extended historical access data based on step S310. The extended vector set refers to the vector set generated according to the extended historical access data. For example, an extended vector set may be generated for the extended historical access data of the previous month based on step S320. Further, the task order processing system may generate a new vector set from the current vector set and the extended vector set, and generate an updated first model based on the method of step S330.

[0098] In some embodiments of the present invention, by combining the historical access data (such as clicks) of a large number of historical users, a task order sorting model with strong generality (i.e., the first model) can be obtained, and this model can be used to recommend task orders for each user. At the same time, according to the user access information of the target user, a task order sorting model with strong pertinence (i.e., the second model) can be obtained, so as to realize personalized task order recommendation and meet the needs of the target user. In addition, through the first model and / or the second model, when the number of task orders is relatively large, the task orders that the user is concerned about can be accurately screened and presented to the user, improving the work efficiency.

[0099] Figure 4a It is an exemplary flowchart of the method for determining the first model shown in some embodiments of the present invention.

[0100] In some embodiments, process 400 may be executed by the task order processing system. As Figure 4a shown, process 400 includes the following steps.

[0101] Step S410, determine a plurality of effective parameters based on the vectors in the vector set.

[0102] The effective parameters refer to the parameters that a task order usually includes. For example, the effective parameters include task order parameters and / or personnel parameters that appear with a relatively high frequency (such as greater than a threshold) in the exposure task order.

[0103] In some embodiments, the task order processing system may determine the occurrence frequency of each parameter based on the vectors in the vector set, and determine a plurality of effective parameters based on the occurrence frequency of each parameter and a preset frequency threshold.

[0104] In some embodiments, the work order processing system may determine the occurrence frequency of each parameter based on the number of occurrences of each parameter in the vector set and the total number of parameters in the vector set. For example, the work order processing system may count the total number of parameters included in the vectors in the vector set and the number of occurrences of each parameter, and use the ratio of the number of occurrences of each parameter (i.e., the number of vectors containing the parameter) to the total number of parameters as the occurrence frequency of this type of parameter. If the occurrence frequency of a parameter is higher, it indicates that the work order usually contains this type of parameter (i.e., most work orders contain this type of parameter); conversely, it indicates that the work order usually does not contain this type of parameter (i.e., only a small number of work orders contain this type of parameter). By way of example only, if vector A contains n1 parameters, vector B contains n2 parameters, and vector C contains n3 parameters, then the occurrence frequency of a certain parameter is the ratio of the number of occurrences of the parameter in vectors A - C to (n1 + n2 + n3).

[0105] In some embodiments of this specification, considering that the data structure of the work order (such as the exposure work order) (such as the parameters it contains) is usually preset, the data structures of different work orders (such as work orders of different departments and types of work) may be different. Additionally, the generation rules for the vectors corresponding to the work orders may also be different. For example, when a user does not set a certain work order parameter, the vector corresponding to the work order may not contain this parameter, or the vector may contain this parameter by replacing the parameter value with a default value. Determining the occurrence frequency of each parameter based on the number of occurrences of each parameter in the vector set and the total number of parameters can accurately reflect the overall distribution of each parameter in the vector set (such as the usage situation), and thus can adapt to different application scenarios (such as vector generation rules).

[0106] In some embodiments, the work order processing system may determine the occurrence frequency of each parameter based on the number of occurrences of each parameter in the vector set and the total number of vectors in the vector set. For example, for each parameter, the work order processing system may count the total number of vectors N vector (such as 100) in the vector set, and the number of occurrences N para of this parameter in multiple vectors of the vector set para , and use the ratio of N vector to N vector as the occurrence frequency of this parameter. Exemplarily, the total number of vectors N vector in the vector set is 100, and the number of occurrences N para of a certain parameter P i in the vector set is 80, which means that among the 100 vectors in the vector set, this parameter P i appears in 80 of them. Then the occurrence frequency of this parameter Pi is 80 / 100 = 0.8.

[0107] In some embodiments of the present specification, the occurrence frequency of each parameter is determined by the number of occurrences of each parameter in the vector set and the total number of vectors in the vector set, which can reflect the actual distribution of each parameter in the vector (task sheet) and reduce the calculation amount.

[0108] For each parameter, in response to the occurrence frequency of the parameter being greater than or equal to the frequency threshold, the task sheet processing system determines it as a valid parameter. In response to the occurrence frequency of the parameter being lower than the frequency threshold, it is determined as an invalid parameter.

[0109] In some embodiments of the present invention, valid parameters are determined by the occurrence frequency of parameters. In subsequent analysis, only the common parameters in the task sheet need to be analyzed, and there is no need to analyze the infrequently occurring invalid parameters, so as to reduce the calculation amount.

[0110] In some embodiments, the task sheet processing system can also determine valid parameters according to the occurrence frequency of each parameter and its corresponding parameter weight. Among them, the parameter weight can be preset according to different work types, positions, etc. Exemplarily, for the work types of construction sites, relatively large parameter weights can be set for the relevant parameters of work-related accidents (such as whether an accident occurs, the number of injured people, etc.).

[0111] In some embodiments of the present invention, considering that the occurrence frequency of some parameters will be relatively low, but their importance or the degree of attention required is relatively high. By setting the parameter weight, some parameters that are occasional but important in practical applications can be retained, so that the valid parameters are more complete and in line with the actual situation.

[0112] In some embodiments, the task sheet processing system can divide the vector set into multiple vector groups, where each vector group can be divided for a certain user group (such as all construction workers, administrative staff group, etc.). Exemplarily, according to the personnel parameters of each vector in the vector set (such as the department id to which the task executor belongs), the vectors with the same department id can be grouped into one vector group, so as to obtain multiple vector groups corresponding to different department user groups. The task sheet processing system can process each vector group as the vector set in step S410 to determine the valid parameters corresponding to each vector group, and based on the following steps S420 to step S440, obtain the first models corresponding to multiple different user groups.

[0113] Step S420, based on multiple valid parameters, determine multiple combinations of valid parameter values, and each combination of valid parameter values includes at least one personnel parameter value and at least one task sheet parameter value.

[0114] A valid parameter value combination refers to the combination of the parameter values corresponding to the valid parameters in a valid parameter combination. Exemplarily, for the valid parameter combination [department, execution status], the corresponding valid parameter value combinations can be [Administrative Department, not started], [Finance Department, completed], [Construction Department, in progress], etc. Among them, the Administrative Department, Finance Department, and Construction Department are the parameter values corresponding to the department parameter, and not started, completed, and in progress are the parameter values corresponding to the execution status parameter.

[0115] Figure 4b It is a schematic diagram for determining the first model according to some embodiments of the present invention.

[0116] As Figure 4b shown, the valid parameter 401 includes a plurality of valid parameters {P 1 , P 2 , P 3 , ……, P n}. The plurality of valid parameters can be combined in groups of 2 (such as [P 1 , P 2 ), groups of 3 (such as [P 1 , P 2 , P 3 ), ……, groups of n (such as [P 1 , P 2 , P 3 , ……, P n ). In some embodiments, each valid parameter combination includes at least one personnel parameter and at least one work order parameter. By way of example only, for the valid parameter combination [P 1 , P 2 , P 3 , the parameter P 1 is a personnel parameter (such as a personnel ID), and the parameters P 2 , P 3 are work order parameters (such as a work order name, an estimated completion time).

[0117] In some embodiments, for each vector in the vector set, the work order processing system can respectively determine whether each parameter in the vector is a valid parameter. In response to a certain parameter being a non-valid parameter, the parameter and its parameter value in the vector are removed, and a valid vector is generated based on the remaining parameters and their parameter values in the vector. In this way, a plurality of valid vectors corresponding to the vector set are determined. This way can be called the removal method.

[0118] For each vector in the vector set, the work order processing system can determine the valid vector 412 according to the valid parameter 401 and the vector set. As Figure 4b shown, the valid vector includes (V 11 , V 21 , V31 ), (V 11 , V 22 , NULL), (V 12 , V 22 , V 31 ), (V 11 , NULL, V 31 ). It should be noted that the above NULL is used to represent the parameters and their parameter values excluded from each vector in the original vector set, and the corresponding effective vectors obtained are (V 11 , V 21 , V 31 ), (V 11 , V 22 ), (V 12 , V 22 , V 31 ), (V 11 , V 31 ). V ij represents the j-th value of parameter P i .

[0119] In some embodiments, for each vector in the vector set, the task order processing system can screen out multiple parameters corresponding to multiple effective parameters from the vector, and then generate an effective vector based on the screened parameters and the parameter values corresponding to the multiple parameters in the vector. Further, according to the multiple vectors in the vector set, multiple effective vectors are determined. This method can be called the screening method.

[0120] Exemplarily, for each vector in the vector set, the task order processing system can respectively determine multiple effective parameters included in the vector according to the effective parameter set (such as effective parameter 401), where the multiple effective parameters can be represented in the form of an effective parameter combination. For example, [P 1 , P 2 , [P 1 , P 2 , P 3 , [P 1 , P 2 , P 3 , ……, P n . The task order processing system can obtain the parameter values corresponding to each effective parameter of the effective parameter combination from the vector, and obtain the effective vectors (V 11 , V 21 ), (V 11 , V 21 , V 31 ), (V 11 , V 21 , V 31 , ……, V n1 ). Among them, V 11 , V21 , V 31 , ……, V n1 respectively represent a single valid parameter P 1 , P 2 , P 3 , ……, P n corresponding parameter values. Exemplarily, V 11 represents the parameter value corresponding to parameter P 1 (such as department), for example, the administrative department, and V 21 represents the parameter value corresponding to parameter P 2 (such as execution status), for example, not started yet, and so on for others. Taking the first vector in the vector set as an example, when only P 1 , P 2 and P 3 are included in this vector among the valid parameters 401, then the task order processing system obtains the parameter values V 1 , P 2 and P 3 corresponding to P 11 , V 21 , V 31 to generate a vector (V 11 , V 21 , V 31 ), which serves as a valid vector. Other vectors in the vector set are processed in a similar manner to obtain multiple valid vectors 412 corresponding to the vector set.

[0121] In some embodiments, for each vector in the vector set, the task order processing system may determine a valid vector based on multiple valid parameters and their corresponding activation ranges; and based on the valid vector, determine at least one combination of valid parameter values, where the multiple combinations of valid parameter values include at least one combination of valid parameter values corresponding to each vector.

[0122] The activation range is used to represent the valid range of a certain parameter value. When the parameter value is within the activation range, it indicates that the parameter value is valid. The activation range can be used to reflect whether the parameter value has an impact on the user's click event. For example, when the parameter value corresponding to a certain parameter is outside the activation range, a task order (such as an exposure task order) containing this parameter value is usually not clicked by the user.

[0123] In some embodiments, the activation range can be preset according to the type of the parameter (such as the valid parameter). For example, the activation range corresponding to the task parameter "completion time" can be set to the past six months up to the current time. If the completion time of a certain task order is six months ago, it means it is outside the activation range. The probability that this task order is viewed or clicked is very small, or the user will not view or click it.

[0124] In some embodiments, for each vector in the vector set, the task sheet processing system determines the initial valid vector corresponding to the vector based on multiple valid parameters. For example, the task sheet processing system processes the vector based on the elimination method or screening method described above to obtain an initial valid vector composed of the valid parameters and their parameter values in the vector (i.e., the invalid parameters and the corresponding parameter values will be eliminated). Further, the task sheet processing system can further determine the valid vector based on the activation range corresponding to each valid parameter in the initial valid vector.

[0125] In some embodiments, if the parameter value of a valid parameter in the initial valid vector is not within its corresponding activation range, then the valid parameter and its parameter value will be eliminated from the initial valid vector; the remaining valid parameters and their parameter values will generate the valid vector. Based on this principle, the task sheet processing system can obtain multiple valid vectors based on multiple initial valid vectors and the activation range corresponding to each valid parameter.

[0126] In some other embodiments, for each initial valid vector in the initial valid vectors, the task sheet processing system can also determine whether the parameter value corresponding to each valid parameter in the initial valid vector is within the activation range. In response to a valid parameter value not being within the activation range, the task sheet processing system can directly eliminate the initial valid vector. Based on this principle, multiple initial valid vectors are processed to obtain multiple valid vectors (i.e., the remaining initial valid vectors will be used as valid vectors).

[0127] In some embodiments, the task sheet processing system can further determine the valid parameter value combination 413 based on the parameter value corresponding to each valid parameter of each valid vector in the valid vector 412. As Figure 4b shown, the valid parameter value combination 413 includes [V 11 , V 21 , [V 11 , V 22 , ……, [V 11 , V 22 , ……, V nk , where k refers to the number of parameter values of the valid parameter P n . For example, the task sheet processing system first determines the valid parameter value combination corresponding to each valid vector 412, and then deduplicates these valid parameter value combinations to obtain the final valid parameter value combination 413. Further referring to Figure 4b , the valid parameter value combination corresponding to the first valid vector includes [V 11 , V 21 , [V 11 , V 31 , [V 21 , V 31 , [V 11, V 21 , V 31 , the combination of valid parameter values corresponding to the second valid vector includes [V 11 , V 22 . These combinations of valid parameters do not overlap and will all be part of the valid parameter value combination 413.

[0128] Step S430, based on the vectors in the vector set, determine the influence factor of each valid parameter value combination.

[0129] The influence factor is used to reflect the influence degree of the valid parameter value combination on the click tasks of multiple users. For example, the influence factor can be in the form of a numerical value. The smaller the value, the smaller the influence, otherwise the greater the influence.

[0130] In some embodiments, the task order processing system can determine the influence factor based on the occurrence times and / or click times of each valid parameter value combination. Among them, the occurrence times of the valid parameter value combination refer to the number of times the valid parameter value combination appears in the valid vector 412.

[0131] For a certain valid parameter value combination, the more times it appears, it means that the more times more users access the task order containing this valid parameter value combination, then the greater the value of its corresponding influence factor. For other users, the greater the probability that the task order containing this valid parameter value combination is accessed, the more it should be presented to the users preferentially.

[0132] For a certain valid parameter value combination, the more times the task order corresponding to this valid parameter value combination is clicked, the greater its corresponding influence factor. For other users, the greater the probability that the task order containing this valid parameter value combination is clicked, the more it should be presented to the users preferentially.

[0133] In some embodiments, the task order processing system can determine the influence factor of each valid parameter value combination according to the first reference weight corresponding to the occurrence times and the second reference weight corresponding to the click times. Among them, the second reference weight is greater than the first reference weight. For example, for two valid parameter value combinations with the same occurrence times, the valid parameter value combination with the greater click times has a relatively greater corresponding influence factor.

[0134] As Figure 4b shown, the task order processing system can, based on the valid parameter value combination 413, obtain the influence factor 414 according to each valid parameter combination respectively. The influence factor 414 includes the influence factors F corresponding to m valid parameter value combinations respectively 1 , influence factor F 2 , ……, influence factor F m .

[0135] In some embodiments of the present invention, through multiple combinations of effective parameter values and their corresponding influence factors, it is possible to comprehensively evaluate the access and / or click situations of a large number of users on task sheets from a large amount of historical access data, thereby reflecting the preference situations or attention degrees of multiple users or user groups for task sheets, and further providing a good basis for the priority presentation (such as sorting) of task sheets.

[0136] In some embodiments, for each combination of effective parameter values among the multiple combinations of effective parameter values, the task sheet processing system can respectively determine the number of occurrences T i times in the vector set corresponding to the historical access data (such as the exposed task sheet), and the click result (such as the number of clicks D i ) of the exposed task sheet containing the combination of effective parameter values, and use the ratio of D i to T i as the influence factor corresponding to the combination of effective parameter values, thereby obtaining the influence factors 414 corresponding to the multiple combinations of effective parameter values 413.

[0137] Step S440, determine the first model based on each combination of effective parameter values and its influence factor.

[0138] The first model can be in various forms such as a mathematical model. In some embodiments, the task sheet processing system can construct sorting factor pairs based on each combination of effective parameter values and their corresponding influence factors, and generate the first model based on the set of sorting factor pairs obtained from the multiple sorting factors. For example, the first model can be expressed as {G 1 :F 1 , ……, G m :F m}, where m is a positive integer greater than or equal to 1. Combining Figure 4b , G 1 represents the combination of effective parameter values [V 11 , V 21 , F 1 represents the influence factor corresponding to G 1 , G m represents the combination of effective parameter values [V 11 , V 21 , ……, V nk , F m represents the influence factor corresponding to G m . The task sheet processing system can generate the first model 405 based on the combination of effective parameter values 413 and the influence factor 414.

[0139] In some embodiments, the task order processing system may determine the sorting strategy for multiple task orders of any user according to the first model, and obtain the sorted task order list based on the sorting strategy. Among them, the task orders with higher rankings in the task order list indicate the task orders that the user may be more interested in or pay more attention to. For example, when the user expects to obtain multiple original task orders that need to be processed currently from the server through the application, the task order processing system may perform multiple rounds of processing on the original task orders based on the first model to determine the sorted task order list.

[0140] As an example, the sorting factor pair F with the largest influence factor in the first model can be obtained first max and the corresponding combination G of effective parameter values for this sorting factor pair can be obtained max Then, multiple candidate task orders containing the combination G of effective parameter values are matched from multiple original task orders max and the priorities of these multiple candidate task orders are set to be larger. The larger the priority, the higher the ranking. Based on multiple sorting factor pairs, the above process is used to process multiple original task orders and / or candidate task orders respectively, so as to determine the sorted task order list.

[0141] The task order processing system then presents this task order list on the interface of the application, so that the user can process (such as view, click operations) the task orders more quickly.

[0142] In some embodiments of the present invention, through the first model, it is possible to quickly generate a sorted task order list for any user, so that the user can more quickly locate, view, and / or process the task orders that they may be more concerned about, improving work efficiency.

[0143] Figure 5a It is a schematic diagram for determining the second model shown in some embodiments of the present invention.

[0144] In some embodiments, the task order processing system may determine the dedicated parameter value combination corresponding to the target user and its corresponding influence factor based on the user identity information corresponding to the target user and the personnel parameter values in each combination of effective parameter values in the first model, and determine the second model based on the dedicated parameter value combination and its influence factor.

[0145] In some embodiments, the first model is a first model applicable to all users. In other embodiments, the first model may be a target first model corresponding to a target user selected from multiple first models. Among them, the multiple first models may be first models corresponding to multiple different user groups. The task order processing system may further determine a dedicated parameter value combination corresponding to the target user and its corresponding influence factor based on the user identity information corresponding to the target user and the personnel parameter values in each valid parameter value combination in the target first model, and determine the second model based on the dedicated parameter value combination and its influence factor. More details about the first model can be found elsewhere in the present invention (e.g., Figure 3 and Figure 4a ).

[0146] The dedicated parameter value combination refers to a valid parameter value combination associated with the target user. For example, at least one personnel parameter value in the dedicated parameter value combination is the same as the personnel parameter value of the target user.

[0147] As Figure 5a shown, the task order processing system may determine the dedicated parameter value combination 503 based on the valid parameter value combination 413 and the user identity information 501 of the target user. The user identity information 501 of the target user may include, but is not limited to, a combination of one or more of the personnel parameter values such as the user ID of the target user (e.g., 10), the employee number (e.g., 9001), the name (e.g., Xiao Qiang), and the department (e.g., the Administration Department).

[0148] In some embodiments, the task order processing system may match one or more personnel parameter values in the user identity information 501 of the target user with the personnel parameter values in the valid parameter value combination 413, so as to screen out h dedicated parameter value combinations 503 from the valid parameter value combination 413, where h is less than or equal to m, which is understandable. The dedicated parameter value combination 503 is a subset of the valid parameter value combination 413. The task order processing system may further determine the influence factor 504 of the screened dedicated parameter value combination 503. For example, the dedicated parameter value combination g h represents the dedicated parameter value combination [V 11 , V 21 , ……, V nh , and the influence factor f h represents the dedicated parameter value combination g hThe corresponding impact factor. Among them, in each combination 503 of dedicated parameter values selected, there is at least one personnel parameter value that is the same as the personnel parameter value of the target user. For example, the value of the "department" parameter in each combination 503 of dedicated parameter values is the same as the value of the "department" parameter of the target user. Further, the task order processing system can determine the second model 505 based on the combination 503 of dedicated parameter values and the impact factor 504. The representation of the second model 505 is similar to that of the first model 405 and will not be elaborated here. For example, the second model can be expressed as {g 1 :f 1 ,..., g h :f m}.

[0149] The impact factor of the dedicated parameter value combination is used to reflect the influence degree of the dedicated valid parameter value combination on the target user's click on the task order. Since the dedicated parameter value combination is selected from the valid parameter value combinations of the first model, the impact factor corresponding to this dedicated parameter combination in the first model can be directly used as the impact factor of the second model. That is to say, the impact factors of the dedicated parameter value combination in the first model and the second model are the same.

[0150] In some embodiments, the task order processing system can also obtain the historical access data corresponding to the target user (such as the exposed task orders corresponding to the target user), and based on the historical access data corresponding to the target user, determine the impact factor corresponding to the dedicated parameter value combination in the same way as determining the impact factor of the first model. At this time, the impact factor of the dedicated parameter value combination in the first model and the impact factor in the second model are different.

[0151] In some embodiments of the present invention, through the identity information of the target user, a dedicated parameter value combination corresponding to the identity information of the target user is matched from the first model, so that the second model conforms to the identity of the target user. In addition, considering the historical access data corresponding to the target user also makes the second model more in line with the target user's preference for task orders, thereby making the second model more accurate and more targeted.

[0152] In some embodiments, the task order processing system can update the second model corresponding to the target user based on the identity change information of the target user. For example, the task order processing system can obtain the identity change information of the target user; based on the identity change information, determine the updated dedicated parameter value combination corresponding to the target user and its corresponding impact factor; and then update the second model corresponding to the target user based on the updated dedicated parameter value combination and the impact factor.

[0153] The identity change information includes the personnel parameters of the target user that have changed and their updated personnel parameter values. For example, if the department of the target user has changed, the identity change information may include the updated department of the target user. In some embodiments, the task order processing system may match the updated personnel parameter values with the personnel parameter values in the valid parameter value combination, so as to screen out the updated dedicated parameter value combination from the valid parameter value combination. The determination method of the updated dedicated parameter value combination is similar to the determination method of the dedicated parameter value combination, which will not be elaborated here.

[0154] In some embodiments, as Figure 5b shown, the task order processing system may also obtain the target exposure task order 506 corresponding to the target user and the target click data 507 of the target user on the target exposure task order, and update the second model 505 based on the target exposure task order 506 and the target click data 507 to obtain the updated second model 508.

[0155] The target exposure task order refers to the task order presented for the target user to browse. The target click data is related to the target click event of the target user on the target exposure task order. The target click data includes the click parameter values of the target click event. The target click data and the target click event are similar to the click data and click event described in step S310, which will not be elaborated here.

[0156] In some embodiments, the task order processing system may determine the target valid vector corresponding to the vector of the target exposure task order that is clicked based on the target click data, and determine the target valid parameter value combination based on the target valid vector. The determination methods of the target valid vector and the target valid parameter value combination are similar to the determination methods of the valid vector and the valid parameter value combination described above. Further, if the target valid parameter value combination is included in the dedicated parameter value combination of the second model 505, the task order processing system may increase the influence factor of this dedicated parameter value combination to obtain its corresponding updated influence factor. If the target valid parameter value combination is not included in the dedicated parameter value combination of the second model 505, the task order processing system may supplement this target valid parameter value combination as a new dedicated parameter value combination and determine its influence shadow based on its occurrence times and / or click times. In some embodiments, if the target valid parameter value combination is not included in the dedicated parameter value combination of the second model 505, only when the number of target click events corresponding to this target valid parameter value combination exceeds the threshold, the task order processing system may supplement this target valid parameter value combination as a new dedicated parameter value combination.

[0157] In some embodiments, the work order processing system may set an update period to update the second model based on the target exposure work order and the target click data. The update period may be the same day, one week, etc. In some embodiments of the present invention, by setting the update period, the second model can be updated regularly while reducing the data processing load.

[0158] Figure 6 It is a schematic diagram of determining a recommended work order corresponding to a target user according to some embodiments of the present invention.

[0159] As Figure 6 shown, the work order processing system may determine a target work order parameter value 602 corresponding to each target work order based on the target work order information corresponding to the target work order 601 related to the target user.

[0160] The target work order 601 may be one or more work orders queried or retrieved by the target user. Alternatively, the target work order 601 may be a work order to be processed by the target user. The target work order information includes various types of information related to the target work order 601. The target work order parameter value 602 refers to the value of the work order parameter of the target work order 601. The target personnel parameter value refers to the value of the personnel parameter of the target user. For more information about work order parameters and personnel parameters, see Figure 3 and its description.

[0161] In some embodiments, the work order processing system may determine a plurality of target parameter value combinations 603 corresponding to each target work order based on the target work order parameter value 602 and the target personnel parameter value of the target user. The target parameter value combination 603 may be a combination of at least one work order parameter value in the target work order parameter value 602 and at least one personnel parameter value in the target personnel parameter value, for example, a combination of 2 parameter values, a combination of 3 parameter values, etc.

[0162] In some embodiments, the work order processing system may determine the recommendation weight of each target work order based on the target parameter value combination 603 and the second model 505.

[0163] The recommended weight can reflect the priority of the target task sheet. The larger the recommended weight, the more the target task sheet is preferentially presented to the target user. In some embodiments, the task sheet processing system can determine the recommended weight of each target task sheet based on the target parameter value combination 603 and each dedicated valid parameter value combination and its corresponding influence factor in the second model 505. For example, for each target task sheet, the task sheet processing system can match its corresponding target parameter value combination with the dedicated valid parameter value combinations in the second model to determine which dedicated valid parameter value combinations are the same as the target parameter value combination; and then determine the recommended weight based on the influence factors of these dedicated valid parameter value combinations. If the influence factors corresponding to these dedicated valid parameter value combinations are larger, the recommended weight is larger.

[0164] As Figure 6 shown, the task sheet processing system can determine the recommended weight 604 based on the second model 505 and the target parameter value combination 603. For example, the recommended weight 604 includes the recommended weight 1 of the target task sheet 1, the recommended weight 2 of the target task sheet 2,..., and the recommended weight n of the target task sheet n. Further, the recommended weights of multiple target task sheets can be sorted to obtain multiple recommended task sheets 605. As Figure 6 shown, the recommended task sheet 1,..., the recommended task sheet m. In some embodiments, the multiple recommended task sheets 605 can be target task sheets with recommended weights greater than the weight threshold. In some embodiments, the multiple recommended task sheets 605 are the top m target task sheets in terms of recommended weight.

[0165] In some embodiments of the present invention, through the second model, the recommended task sheet corresponding to the target user can be quickly determined, thereby improving the processing efficiency of the task sheet by the target user in actual work.

[0166] It should be noted that the above description of the process is only for illustration and explanation, and does not limit the scope of application of the present invention. For those skilled in the art, various modifications and changes can be made to the process under the guidance of the present invention. However, these modifications and changes are still within the scope of the present invention.

[0167] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only an example and does not constitute a limitation of the present invention. Although not explicitly stated here, those skilled in the art may make various modifications, improvements, and corrections to the present invention. Such modifications, improvements, and corrections are proposed in the present invention, so such modifications, improvements, and corrections still belong to the spirit and scope of the exemplary embodiments of the present invention.

[0168] Meanwhile, the present invention uses specific terms to describe embodiments of the present invention. For example, "an embodiment", "one embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of the present invention. Therefore, it should be emphasized and noted that the "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more at different positions in the present invention does not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the present invention can be appropriately combined.

[0169] In addition, unless clearly stated in the claims, the order of the processing elements and sequences, the use of numerical and alphabetical characters, or the use of other names in the present invention are not used to limit the order of the processes and methods of the present invention. Although some currently useful embodiments of the invention are discussed through various examples in the above disclosure, it should be understood that such details only serve the purpose of illustration. The appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that conform to the essence and scope of the embodiments of the present invention. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only through software solutions, such as installing the described system on existing servers or mobile devices.

[0170] Similarly, it should be noted that, in order to simplify the expression of the present invention disclosure and thus help the understanding of one or more embodiments of the invention, in the foregoing description of the embodiments of the present invention, sometimes multiple features are grouped into one embodiment, drawing, or description thereof. However, this disclosure method does not mean that the features required by the object of the present invention are more than those mentioned in the claims. In fact, the features of the embodiment are less than all the features of the single embodiment disclosed above.

[0171] In some embodiments, numbers describing the composition and the quantity of attributes are used. It should be understood that such numbers used for the description of the embodiments are modified by the modifiers "about", "approximately", or "substantially" in some examples. Unless otherwise stated, "about", "approximately", or "substantially" indicate that the said numbers allow a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, and such approximate values can change according to the characteristics required by individual embodiments. In some embodiments, the numerical parameters should consider the specified significant digits and adopt the method of retaining the general number of digits. Although the numerical ranges and parameters used to confirm the breadth of the scope in some embodiments of the present invention are approximate values, in specific embodiments, such numerical settings are as precise as possible within the feasible range.

[0172] For each patent, patent application, patent application publication, and other materials cited in the present invention, such as articles, books, specifications, publications, documents, etc., the entire content thereof is hereby incorporated by reference into the present invention. This excludes the application history files that are inconsistent with or conflict with the content of the present invention, as well as the files (currently or subsequently appended to the present invention) that limit the broadest scope of the claims of the present invention. It should be noted that if there are any inconsistencies or conflicts between the descriptions, definitions, and / or uses of terms in the attached materials of the present invention and the content described in the present invention, the descriptions, definitions, and / or uses of terms in the present invention shall prevail.

[0173] Finally, it should be understood that the embodiments described in the present invention are only used to illustrate the principles of the embodiments of the present invention. Other variations may also fall within the scope of the present invention. Therefore, by way of example and not limitation, alternative configurations of the embodiments of the present invention may be considered to be consistent with the teachings of the present invention. Accordingly, the embodiments of the present invention are not limited to the embodiments explicitly presented and described in the present invention.

Claims

1. A task order processing method, characterized in that: include: Acquire historical access data of historical users, each of the historical access data includes an exposure task list and click data of each of the exposure task lists; Determine a vector set of the historical access data, wherein the vectors in the vector set include personnel parameter values, task order parameter values, and click parameter values, wherein the click parameter values ​​are determined based on the click data; Based on the vector set, determining a first model; the determining the first model based on the vector set includes: Determining a plurality of effective parameters based on the vectors in the vector set; Based on the multiple valid parameters, determine multiple valid parameter value combinations, each of the valid parameter value combinations includes at least one of the personnel parameter value and at least one of the task order parameter value; Determining an impact factor of each of the valid parameter value combinations based on the vectors in the vector set; Determining the first model based on each of the valid parameter value combinations and their influencing factors; Acquire user access information of a target user, wherein the user access information includes user identity information corresponding to the target user; Determining a second model corresponding to the target user based on the user access information and the first model; determining the second model corresponding to the target user based on the user access information and the first model includes: Determine, based on the user identity information corresponding to the target user and the personnel parameter value in each of the valid parameter value combinations in the first model, a dedicated parameter value combination corresponding to the target user and its influencing factor; the dedicated parameter value combination refers to a valid parameter value combination associated with the target user, and at least one personnel parameter value in the dedicated parameter value combination is the same as the personnel parameter value of the target user; Determining the second model based on the combination of dedicated parameter values ​​and their influencing factors; Based on the second model, a recommended task list corresponding to the target user is determined.

2. The method according to claim 1, characterized in that The determining of a plurality of valid parameters based on the vectors in the vector set comprises: Determining the frequency of occurrence of each parameter based on the vectors in the vector set; The plurality of valid parameters are determined based on the occurrence frequency of each of the parameters and a preset frequency threshold.

3. The method according to claim 1, characterized in that The determining, based on the multiple valid parameters, multiple valid parameter value combinations comprises: For each vector in the vector set, Determining an effective vector based on the plurality of effective parameters and their corresponding activation ranges; At least one of the valid parameter value combinations is determined based on the valid vector, wherein the multiple valid parameter value combinations include at least one of the valid parameter value combinations corresponding to each of the vectors.

4. The method according to claim 1, characterized in that: The determining, based on the vectors in the vector set, the influencing factor of each of the valid parameter value combinations comprises: The influence factor is determined based on the number of occurrences and / or clicks of each of the valid parameter value combinations.

5. The method according to claim 1, characterized in that The method further comprises: Obtaining a target exposure task list corresponding to the target user and target click data of the target user on the target exposure task list; Based on the target exposure task list and the target click data, the second model is updated.

6. The method according to claim 1, characterized in that: The method further comprises: Obtaining identity change information of the target user; Based on the identity change information, determining an update-specific parameter value combination and its influencing factor corresponding to the target user; Based on the update-specific parameter value combination and its influencing factors, the second model corresponding to the target user is updated.

7. The method according to claim 2, characterized in that The determining, based on the second model, a recommended task list corresponding to the target user comprises: Based on the target task order information corresponding to the target task order related to the target user, determining the target task order parameter value corresponding to each target task order; Based on the target task list parameter value and the target personnel parameter value of the target user, determining a plurality of target parameter value combinations corresponding to each target task list; Determining a recommendation weight of each of the target task orders based on the multiple target parameter value combinations and the second model; Based on the recommendation weight, the recommended task list is determined.

8. A task order processing system, characterized in that: include: A first acquisition module is configured to acquire historical access data of historical users, each of the historical access data includes an exposure task list and click data of each of the exposure task lists; A vector set determination module, configured to determine a vector set of the historical access data, wherein the vectors in the vector set include a personnel parameter value, a task order parameter value, and a click parameter value, wherein the click parameter value is determined based on the click data; The first model determination module is configured to determine a first model based on the vector set; the first model determination module is further configured to: Determining a plurality of effective parameters based on the vectors in the vector set; Based on the multiple valid parameters, determine multiple valid parameter value combinations, each of the valid parameter value combinations includes at least one of the personnel parameter value and at least one of the task order parameter value; Determining an impact factor of each of the valid parameter value combinations based on the vectors in the vector set; Determining the first model based on each of the valid parameter value combinations and their influencing factors; A second acquisition module is configured to acquire user access information of a target user, wherein the user access information includes user identity information corresponding to the target user; The second model determination module is configured to determine the second model corresponding to the target user based on the user access information and the first model; the second model determination module is further configured to: Determine, based on the user identity information corresponding to the target user and the personnel parameter value in each of the valid parameter value combinations in the first model, a dedicated parameter value combination corresponding to the target user and its influencing factor; the dedicated parameter value combination refers to a valid parameter value combination associated with the target user, and at least one personnel parameter value in the dedicated parameter value combination is the same as the personnel parameter value of the target user; Determining the second model based on the combination of dedicated parameter values ​​and their influencing factors; The recommendation module is configured to determine a recommended task list corresponding to the target user based on the second model.

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