CN112818040A

CN112818040A - Big data combined user behavior analysis method and information processing server

Info

Publication number: CN112818040A
Application number: CN202110251535.6A
Authority: CN
Inventors: 裴炳坤
Original assignee: 裴炳坤
Current assignee: Guangzhou zhiyunshang Big Data Technology Co.,Ltd.
Priority date: 2021-03-08
Filing date: 2021-03-08
Publication date: 2021-05-18

Abstract

According to the user behavior analysis method and the information processing server combined with the big data, the overall content information of the second user behavior interaction information is determined through the service interaction strategy of the service interaction content recorded based on each group of user behavior interaction information, the interaction integrity of the second user behavior interaction information recording overall service interaction content is obtained based on the overall content information, when the overall content information meets a second target condition, the user behavior analysis is carried out only based on the first user behavior interaction information, the number of the user behavior interaction information participating in the user behavior analysis is reduced, and the time consumed by information analysis is reduced; and the user behavior analysis is carried out based on the global content information, so that the problems of inaccurate identification and low reliability caused by directly deleting the second user behavior interaction information are avoided, and the efficiency of the user behavior analysis is improved on the premise of ensuring the accuracy of the user behavior analysis.

Description

Big data combined user behavior analysis method and information processing server

Technical Field

The present disclosure relates to the field of big data and user behavior analysis technologies, and in particular, to a user behavior analysis method and an information processing server that combine big data.

Background

Big data refers to data with a data set size and scale that exceeds the processing power of existing typical database software and tools, and big data analysis refers to analysis of data with a huge scale. Big data is used as the vocabulary of the IT industry which is the most fiery at present, and the utilization of the commercial value of the big data, such as data warehouse, data security, data analysis, data mining and the like, becomes the profit focus which is pursued by the industry people gradually.

With the advent of the big data era, user Behavior Analysis (Analysis of Users' Behavior) also arose, wherein the user Behavior Analysis means that under the condition of obtaining platform access amount basic data such as websites or APPs, relevant data are counted and analyzed, rules of Users accessing the websites or APPs and other platforms are found, and the rules are combined with network marketing strategies and the like, so that problems possibly existing in the current network marketing activities are found, a basis is provided for further correcting or re-formulating the network marketing strategies, and Users are better served.

However, as the scale of the user behavior data and the user behavior information increases day by day, the related user behavior analysis technology has the problems of poor recognition accuracy and reliability, low efficiency and the like.

Disclosure of Invention

In order to solve the technical problems in the related art, the present disclosure provides a user behavior analysis method and an information processing server that combine big data.

The invention provides a user behavior analysis method combined with big data, which comprises the following steps:

acquiring user behavior interaction information, performing service response information identification on the user behavior interaction information, and performing user interest intention analysis on the acquired service response information to obtain a user interest preference tag of the service response information; the user behavior interaction information is used for recording the interaction content of the target business service; determining user requirement matching information or a user requirement matching information set corresponding to the business service response information according to the user interest preference label; and determining a user behavior analysis result corresponding to the target business service interactive content according to the user requirement matching information or the user requirement matching information set.

The invention also provides an information processing server, which comprises a processor and a memory; the processor is connected with the memory in communication, and the processor is used for reading the computer program from the memory and executing the computer program to realize the method.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects.

The utility model provides a big data-combined user behavior analysis method and an information processing server, which determine the global content information of second user behavior interaction information through a business interaction strategy of business service interaction content recorded based on each group of user behavior interaction information, acquire the interaction integrity of the second user behavior interaction information recording global business service interaction content based on the global content information, and perform user behavior analysis only based on the first user behavior interaction information when the global content information meets a second target condition, thereby reducing the number of user behavior interaction information participating in user behavior analysis and reducing the time consumed by information analysis; and the user behavior analysis is carried out based on the global content information, so that the problems of inaccurate identification and low reliability caused by directly deleting the second user behavior interaction information are avoided, and the efficiency of the user behavior analysis is improved on the premise of ensuring the accuracy of the user behavior analysis.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

Fig. 1 is a schematic diagram of a system scenario architecture of a user behavior analysis method combined with big data according to an embodiment of the present invention.

Fig. 2 is a flowchart of a user behavior analysis method combining big data according to an embodiment of the present invention.

Fig. 3 is a block diagram of a device for analyzing user behavior in conjunction with big data according to an embodiment of the present invention.

Fig. 4 is a schematic diagram of a hardware structure of an information processing server according to an embodiment of the present invention.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.

Fig. 1 is a schematic diagram of a system scenario architecture of a user behavior analysis method combined with big data according to an embodiment of the present invention, and referring to fig. 1, the system scenario architecture includes: an information processing server 101 and a user operation terminal 102. The information processing server 101 may be provided with a user behavior analysis thread, the user operation terminal 102 may be a local terminal corresponding to the user behavior analysis thread, the user behavior analysis thread has a business service analysis function, and the business service analysis function is a function of analyzing a user requirement matching information set corresponding to business service response information. The information processing server 101 may perform response information interaction with the user operation terminal 102 based on the user behavior analysis thread to implement the business service analysis function. For example, the information processing server 101 may collect service response information in different service scenarios, send the collected service response information to the user operation terminal 102, and the user operation terminal 102 identifies the service response information to obtain a user requirement matching information set corresponding to the service response information.

In a possible scenario, the information processing server 101 may collect target service interaction content recorded in a user interaction process in real time, mark service response information corresponding to the collected target service interaction content as multiple sets of user behavior interaction information, and the information processing server 101 sends the multiple sets of user behavior interaction information to the user operation terminal 102. The user operation terminal 102 may perform user behavior analysis on the service interaction content recorded in each group of user behavior interaction information based on the service response information in each group of user behavior interaction information. In the analysis process, the user operation terminal 102 may further determine, based on the service interaction evaluation of the service interaction content recorded by the multiple sets of user behavior interaction information, the interaction integrity of the second user behavior interaction information recorded by the global service interaction content in the multiple sets of user behavior interaction information, and the user operation terminal 102 may analyze the user behavior analysis result corresponding to the target service interaction content only according to the first user behavior interaction information in the multiple sets of user behavior interaction information when the second user behavior interaction information does not record the global service interaction content. In one possible example, the global business service interactive content refers to business service interactive content other than abnormal interactive content business interaction, for example, the global business service interactive content may be complete business service interactive content recorded in a user interaction process.

In one possible example, the user operation terminal 102 may be a mobile phone, a tablet, a personal computer, a notebook, or the like, and in another possible scenario, the information processing server 101 may further execute, based on the user behavior analysis result, a relevant business guidance behavior corresponding to the user behavior analysis result in the user behavior analysis thread. It should be noted that the information processing server 101 may be a server, a server cluster composed of several servers, or a cloud computing server center. The embodiment of the present invention is not particularly limited to this.

In order to solve the problems described in the background art, an embodiment of the present invention provides a method for analyzing user behavior in combination with big data, where the method may include the following steps: acquiring user behavior interaction information, performing service response information identification on the user behavior interaction information, and performing user interest intention analysis on the acquired service response information to obtain a user interest preference tag of the service response information; the user behavior interaction information is used for recording the interaction content of the target business service; determining user requirement matching information or a user requirement matching information set corresponding to the business service response information according to the user interest preference label; and determining a user behavior analysis result corresponding to the target business service interactive content according to the user requirement matching information or the user requirement matching information set. Based on the above, the identification accuracy and reliability of the user behavior analysis can be ensured, and the efficiency of the user behavior analysis can be ensured. It will be appreciated that further description of the above may be had with reference to the method illustrated in figure 2.

Fig. 2 is a flowchart of a user behavior analysis method combining big data according to an embodiment of the present invention. The execution main body of the embodiment of the invention is an information processing server. Referring to fig. 2, the method includes:

s201, the information processing server obtains at least two groups of user behavior interaction information, and the at least two groups of user behavior interaction information are used for recording the interaction content of the target business service.

In the embodiment of the present invention, the target service interaction content may be a service interaction content corresponding to a user operation terminal, and the at least two sets of user behavior interaction information include service response information corresponding to the target service interaction content. In this step, the information processing server may obtain at least two sets of user behavior interaction information with a certain amount of data information. This step may include: the information processing server acquires a target response message volume, wherein the target response message volume is used for indicating the response message volume of the business service response message included in a group of user behavior interaction messages. The information processing server acquires the at least two groups of user behavior interaction information according to the target response information amount, wherein the response information amount of each group of user behavior interaction information is the target response information amount. In one possible example, the information processing server may identify, based on the service response information in each set of user behavior interaction information, service interaction content recorded in each set of user behavior interaction information, to obtain an identification result of each set of user behavior interaction information. The target response information amount may be a response information amount of the service response information corresponding to the process of performing the user behavior analysis once. For example, the target response message amount of each set of user behavior interaction messages may be 1MB, 2MB, and the like. The recognition result may be: the user requirement matching information set is composed of single user requirement matching information or at least two pieces of user requirement matching information.

In addition, in a possible implementation manner, the information processing server may identify a plurality of pieces of business service response information from the business service response information in the user behavior interaction information, and perform user behavior analysis in units of each piece of business service response information, for example, the information processing server may identify business service interaction content recorded by each piece of business service response information based on a user interest preference tag of the business service response information with a certain response attribute, where the user interest preference tag of each piece of business service response information is used to indicate a possibility that each candidate business service event of at least two candidate business service events of the piece of business service response information is a real business service event. The information processing server can take a plurality of continuous business service response information as a business service response information set, and based on a certain number of continuous business service response information sets, a user interest preference label determining process is carried out to obtain a user interest preference label of each piece of business service response information. The information processing server may determine the size of the target response information amount in combination with the statistical number of the service response information sets required in the process of determining the interest preference tag of the user once, the identification manner of the service response information in the user behavior interaction information, and other factors. The process may then include: the information processing server determines the target response information amount based on the target information change condition, the first target statistical number and the target information sampling strategy. In one possible example, the first target statistical number is used to indicate a statistical number of business service response information sets corresponding to a one-time user interest preference tag determination process, each business service response information set including a plurality of adjacent pieces of business service response information. The target information sampling strategy refers to an information sampling strategy of business service response information in the user behavior interaction information. The target information change condition refers to the unit time information change quantity between two adjacent business service response messages. The target response status and the target information change condition may be set based on needs, which is not specifically limited in the embodiment of the present invention. For example, the target information variation may be 10 MB/min.

In the embodiment of the present invention, the size of the first group of user behavior interaction information in the at least two groups of user behavior interaction information may be different from the size of other user behavior interaction information except the first group of user behavior interaction information. In a possible implementation manner, for the user behavior interaction information except for the first group of user behavior interaction information, the information processing server may determine the first target response information amount according to the target information change condition, the first target statistical number and the target information sampling policy, where the first target response information amount is used to indicate a response information amount of the service response information in the user behavior interaction information except for the first group of user behavior interaction information in the at least two groups of user behavior interaction information. In one possible example, for the user behavior interaction information except for the first group of user behavior interaction information in the at least two groups of user behavior interaction information, the information processing server may determine the first target response information amount according to the first target statistical amount, the target information change condition and the target information sampling strategy.

In another possible implementation manner, for the first set of user behavior interaction information, the information processing server may further determine, by combining the response status of each piece of service response information and the response attribute of the service response information in one service response information set, the size of the response information amount of the first set of user behavior interaction information, and then the process may include: the information processing server may determine a second target response information amount according to the target information change condition, the target response state, the first target statistical amount, the second target statistical amount, and the target information sampling policy. The second target response information amount is used for indicating the response information amount of the business service response information in the first group of user behavior interaction information in the at least two groups of user behavior interaction information, and each business service response information set comprises a second target statistical quantity of business service response information. The target response state refers to that the response of a piece of business service response information is time-consuming. The target response status may be set based on needs, which is not specifically limited in this embodiment of the present invention. For example, if the response time consumption corresponding to the target response state may be 1s, the information processing server may identify the first group of user behavior interaction information as the plurality of pieces of service response information according to the 0.5s information change condition and the 1s response state. In a possible example, for the first set of user behavior interaction information, the information processing server may further determine the second target response information amount according to the target response state, the first target statistical amount, the target information variation, the target information sampling policy, and the second target statistical amount.

In a possible implementation manner, when the information processing server is a server, the information processing server may obtain the target response information amount, send the target response information amount to the user operation terminal, send, by the user operation terminal, the at least two sets of user behavior interaction information to the information processing server based on the target response information amount, receive, by the information processing server, the at least two sets of user behavior interaction information sent by the user operation terminal, where a response information amount of each set of user behavior interaction information is the target response information amount. In one possible example, the user operation terminal may generate corresponding user behavior interaction information according to the collected target service interaction content during the process of collecting the service interaction content, send the user behavior interaction information generated in real time to the information processing server, when receiving a termination instruction, the user operation terminal may further determine a last group of user behavior interaction information based on the termination instruction, send the last group of user behavior interaction information and a termination signal to the information processing server, the termination signal being used to indicate a sending progress of the user behavior interaction information corresponding to the target service interaction content, the information processing server receives the last group of user behavior interaction information, and determines that the sending of the user behavior interaction information corresponding to the target service interaction content is completed based on the termination signal, the information processing server may use the last received user behavior interaction information as the last set of user behavior interaction information. Of course, the user operation terminal may include the termination signal in the last group of user behavior interaction information, and when the information processing server decompresses the last group of user behavior interaction information, the information processing server obtains the termination signal and determines the last group of user behavior interaction information in the at least two groups of user behavior interaction information.

It should be noted that, since the information processing server needs the user behavior interaction information corresponding to the target response information amount to execute a user behavior analysis process, the information processing server may obtain each group of user behavior interaction information based on the target response information amount, thereby ensuring that the response information amount of a group of user behavior interaction information obtained each time can just execute a user behavior analysis process. And, since a continuous first target statistical number of business service response information sets are required, a user interest preference tag determination process can be performed once. The information processing server can set the size of the user behavior interaction information in real time based on dynamic parameters such as a target response state, a target information change condition, a first target statistic number and the like of the user behavior analysis, so that the user interest preference tag determining process can be completed just once by one group of user behavior interaction information acquired every time. The method has the advantages that the method does not wait for the service response information of the next group of user behavior interaction information because too little response information is not enough to trigger the user interest preference tag determination process once; and the redundant response information does not need to wait for the next group of user behavior interaction information because of excessive response information, so that the redundant response information needs to delay the determination of the user interest preference tag. The embodiment of the invention effectively improves the processing efficiency of each group of user behavior interaction information and the feedback speed of the user behavior analysis result corresponding to each group of user behavior interaction information by determining the reasonable response information amount of each group of user behavior interaction information, thereby optimizing the user behavior analysis strategy and improving the user behavior analysis efficiency on the premise of not influencing the accuracy and the credibility of the user behavior analysis result.

It should be noted that the at least two sets of user behavior interaction information include second user behavior interaction information and first user behavior interaction information, the second user behavior interaction information is last set of user behavior interaction information in the at least two sets of user behavior interaction information, and the first user behavior interaction information may be user behavior interaction information other than the last set of user behavior interaction information in the at least two sets of user behavior interaction information. In a possible implementation manner, the embodiment of the present invention may focus on an optimized analysis process of the second user behavior interaction information. For the second user behavior interaction information, the information processing server may perform user behavior analysis on the second user behavior interaction information through the following processes of S203-S205; for the first user behavior interaction information, the information processing server may perform user behavior analysis on the first user behavior interaction information through the following process of S202. The information processing server can obtain the identification result of the target business service interactive content based on the identification process of the second user behavior interactive information and the first user behavior interactive information.

S202, for the first user behavior interaction information, the information processing server analyzes a user behavior analysis result corresponding to each group of user behavior interaction information according to the service response information in each group of user behavior interaction information.

For the first user behavior interaction information, the information processing server may identify the service response information according to the service response information of the first user behavior interaction information, and perform user behavior analysis on service interaction content recorded by the first user behavior interaction information based on the plurality of pieces of service response information obtained by the identification. Illustratively, this step may be implemented by S2021-S2025 below.

S2021, the information processing server identifies the business service response information of the first user behavior interaction information, extracts user interest intention of each piece of business service response information to obtain a plurality of pieces of business service response information, and obtains the user interest intention of each piece of business service response information.

In this step, the information processing server identifies the service response information of the first user behavior interaction information as a plurality of pieces of service response information according to the target response state and the target information change condition. The user interest intention may be a business requirement intention of the business service response information, and the like, which is not specifically limited in the embodiment of the present invention. The user interest intention of each piece of the business service response information may be in the form of intention text content.

2022. The information processing server obtains the business service response information set of the first target statistical quantity according to the first target statistical quantity and the second target statistical quantity.

The information processing server may determine, from the plurality of pieces of business service response information, a business service response information set of a second target statistical number, and determine, from the first user behavior interaction information, the business service response information set of the first target statistical number. In a possible implementation manner, for each piece of service response information, the information processing server obtains a second target statistical number of pieces of service response information including the piece of service response information from a plurality of pieces of service response information in the user behavior interaction information according to the second target statistical number, and uses the second target statistical number of pieces of service response information as a service response information set in which the piece of service response information is located. The second target statistical number of pieces of business service response information may be a plurality of pieces of business service response information that are consecutive and adjacent in the plurality of pieces of business service response information included in the user behavior interaction information. In a possible example, each piece of service response information corresponds to a set of service response information, for each piece of service response information, the information processing server may obtain the piece of service response information, arrange, in the plurality of pieces of service response information of the user behavior interaction information, a fifth target statistical number of pieces of service response information sequentially located after the piece of service response information, and use the piece of service response information and the fifth target statistical number of pieces of service response information as a set of service response information. The second target statistical quantity may be equal to the fifth target statistical quantity plus one.

For example, the n pieces of service response information included in the first user behavior interaction information may be: article 1, article 2, article 3, article … …, article n. The information processing server may regard k consecutive pieces of service response information as one service response information set, for example, the 1 st, 2 nd, 3 rd, … … th is the service response information set where the first piece of service response information is located; item 2, item 3, item 4, item … …, item k +1, is a service response information set where the second service response information is located, each service response information corresponds to a service response information set, and so on, the service response information set corresponding to the first target statistical quantity is obtained.

S2023, the information processing server determines a user interest preference tag of each business service response information through a user interest preference algorithm based on the user interest intention of each business service response information set in the first target statistical number of business service response information sets.

For each service response information set, the information processing server may fuse the user interest intentions of the service response information corresponding to the second target statistical number in the service response information set to obtain the user interest intentions of the service response information set. The information processing server can determine the user interest preference label of each business service response information set through a user interest preference algorithm according to the user interest intentions of the business service response information sets with the first target statistical number. For each piece of service response information, the information processing server may determine the user interest preference tag of the service response information set in which the piece of service response information is located as the user interest preference tag of the piece of service response information.

The user interest preference label of each piece of business service response information comprises at least two candidate business service events corresponding to the piece of business service response information and a label of each candidate business service event. The label of each candidate business service event is used for representing the possibility that the candidate business service event is the real business service event of the business service interaction content recorded by the piece of business service response information. The larger the tag value of a candidate business service event, the greater the likelihood that the candidate business service event is a real business service event.

S2024, the information processing server determines the business service event of each piece of business service response information according to the user interest preference label of each piece of business service response information.

For each piece of service response information, the information processing server may select, according to the user interest preference tag of the piece of service response information, a candidate service event corresponding to the maximum tag attribute value from at least two candidate service events of the piece of service response information, as the service event of the piece of service response information. In one possible implementation, the information processing server may use each business service event of each piece of business service response information as a category to which the response information belongs, and use a label of the business service event as response content status information of the category to which the response information belongs. The information processing server may correspondingly traverse the category to which the response information belongs to perform the business service query, and determine the business service event of each piece of business service response information. In one possible example, for each piece of service response information, the information processing server obtains at least two categories to which temporary response information belongs according to a category to which the first response information corresponding to a previous piece of service response information of the piece of service response information belongs, each category to which temporary response information belongs being used for indicating a candidate service event of the current piece of service response information, the information processing server obtains the label of each candidate business service event from the user interest preference label of the current business service response information, and according to the label of each candidate business service event, determining the category to which the second response information belongs from the categories to which the at least two temporary response information belongs, and taking the category to which the second response information belongs as the category to which the response information of the current business service response information belongs. And the response content state information of the category to which the second response information belongs is the label corresponding to the candidate business service event. In the embodiment of the present invention, the statistical numbers of the categories to which the first response information belongs and the categories to which the second response information belongs are not limited, for example, the information processing server may use all the categories to which the temporary response information belongs as the categories to which the second response information belongs, or may screen out the category to which the second response information with the sixth target statistical number belongs from at least two categories to which the temporary response information belongs, for example, screen out the categories to which 15 second response information with tag heat values corresponding to the business service event located in the top 15 names belong. For example, the category to which the response information corresponding to each piece of service response information belongs may be referred to as a category to which the active response information of the piece of service response information belongs, and when the information processing server traverses the category to which the active response information of the x pieces of service response information belongs, the information processing server may place the category to which the active response information corresponding to the x pieces of service response information belongs in a category list to which the active response information belongs, and continue traversing the category to which the provisional response information of each category to which the first response information belongs, for example, the category to which the first response information belongs may correspond to 3 categories to which the provisional response information belongs, so as to finally determine the category to which the second response information of the x +1 piece of service response information belongs.

S2025, the information processing server determines, according to at least two service events of the plurality of service response messages, user requirement matching information or a user requirement matching information set corresponding to the plurality of service response messages.

The information processing server determines the category to which the response information corresponding to the plurality of pieces of business service response information belongs and the response content state information of the category to which the response information belongs, and traverses from the category to which the hot response information corresponding to the first piece of business service response information belongs to the category to which the cold response information corresponding to the last piece of business service response information belongs, so that a plurality of candidate response contents are traversed, and the response content with the most frequent update of the response content state information in the plurality of candidate response contents is used as the target response content. The information processing server is used as at least two business service events of the first user behavior interaction information according to the business service events corresponding to the types of the response information in the target response content. When the at least two business service events meet the first target condition, the information processing server can further analyze the labels of the at least two candidate user requirement matching information corresponding to the at least two business service events based on the user behavior analysis model. The first target condition may be a service quality monitoring condition to which the at least two service events may correspond, and the information processing server determines, according to the tags of the at least two candidate user requirement matching information, the recognition result of the first user behavior interaction information, that is, a user requirement matching information set or a single user requirement matching information corresponding to the multiple pieces of service response information. The user behavior analysis model may be a convolutional neural network model, a forward feedback neural network model, or a decision tree model, and the embodiment of the present invention is not particularly limited to this.

It should be noted that, in order to describe the above S2021 to S2025 more clearly, S2021 to S2025 further describe, for example, the user operating terminal splits the target service interaction content of the user, divides the target service interaction content into at least two groups of user behavior interaction information, sends the at least two groups of user behavior interaction information to the information processing server, and determines whether to upload the last group of user behavior interaction information, and if so, stops uploading. The information processing server acquires at least two groups of user behavior interaction information uploaded by a user operation terminal, for each group of user behavior interaction information, the information processing server identifies the service response information in each group of user behavior interaction information into a plurality of pieces of service response information according to a target response state and a target information change condition, extracts the user interest intention of each piece of service response information for each piece of service response information, determines the user interest preference label of each piece of service response information through a user interest preference algorithm based on at least two service response information sets in which the plurality of pieces of service response information in the user behavior interaction information are located, determines the service event of each piece of service response information in a mode of inquiring corresponding to the category to which the traversal response information belongs based on the user interest preference label of each piece of service response information, and determining user behavior analysis results corresponding to a plurality of pieces of business service response information in the user behavior interaction information by combining the user behavior analysis model labels in the query process. In addition, the information processing server may also dynamically calculate the size of the user behavior interaction information in real time in a manner corresponding to S201 described above. By reasonably configuring the size of each group of user behavior interaction information, the problem of low user behavior analysis efficiency caused by unreasonable size of response information of the user behavior interaction information is solved, and the feedback efficiency of each group of user behavior interaction information can be effectively improved.

S203, the information processing server determines a first business interaction strategy of business service interaction content recorded by the second user behavior interaction information and a second business interaction strategy of business service interaction content recorded by the first user behavior interaction information based on business interaction evaluation of each piece of business service response information included by the second user behavior interaction information and the first user behavior interaction information.

In the embodiment of the invention, the business interaction strategy is used for indicating the interaction evaluation type of the business service interaction content; when the modification times or error reporting times of the service interaction content are large, the service interaction evaluation of the service interaction content is biased to be negative, and the service interaction strategy is unreasonable; when the modification times or error reporting times of the business service interactive contents are small, the business interaction evaluation of the business service interactive contents is biased to be positive, and the business interaction strategy is reasonable. The business interaction policy may be a dynamically tunable policy of business service interaction content.

In the embodiment of the present invention, for the second user behavior interaction information, the information processing server may also determine, according to the target response state and the target information change condition, a plurality of pieces of service response information included in the second user behavior interaction information. The information processing server may determine the service interaction policy of the second user behavior interaction information according to the service interaction evaluation of each piece of service response information included in the second user behavior interaction information. For the first user behavior interaction information, the information processing server may also determine the service interaction policy of the first user behavior interaction information according to the service interaction evaluation of each piece of service response information included in the first user behavior interaction information.

In a possible implementation manner, the information processing server may further represent a service interaction policy of the first user behavior interaction information in combination with the association evaluation between the first user behavior interaction information and the second user behavior interaction information. The process may include: and the information processing server acquires a second business interaction strategy of business service interaction content recorded by the first user behavior interaction information according to the association evaluation between the first user behavior interaction information and the second user behavior interaction information and the business interaction evaluation of each piece of business service response information in the first user behavior interaction information. The association evaluation is used for indicating the influence degree of the business interaction evaluation of the business service response information in the first user behavior interaction information on the business interaction evaluation of the business service response information in the second user behavior interaction information. In one possible implementation manner, the information processing server may represent the association evaluation between the first user behavior interaction information and the second user behavior interaction information corresponding to the arrangement position of the first user behavior interaction information in at least two groups of user behavior interaction information. The information processing server can acquire the arrangement position of the first user behavior interaction information in the at least two groups of user behavior interaction information; and the information processing server acquires a second business interaction strategy of business service interaction content recorded by the first user behavior interaction information according to the business interaction evaluation of each piece of business service response information in the first user behavior interaction information and the arrangement position of the first user behavior interaction information in the at least two groups of user behavior interaction information. The arrangement position is used for indicating the association evaluation of the first user behavior interaction information and the second user behavior interaction information, and the more backward the arrangement position of the first user behavior interaction information is, the higher the satisfaction degree corresponding to the association evaluation between the first user behavior interaction information and the second user behavior interaction information is; the more forward the arrangement position of the first user behavior interaction information is, the lower the satisfaction degree corresponding to the association evaluation between the second user behavior interaction information is. The arrangement position of the first user behavior interaction information is used for indicating the influence degree of the second response information on the service interaction evaluation of the service response information in the second user behavior interaction information, the more the arrangement position of the first user behavior interaction information is, the larger the influence of the first user behavior interaction information on the service interaction evaluation of the service response information in the second user behavior interaction information is, for example, the service interaction strategy size of the second user behavior interaction information in the two groups of user behavior interaction information is similar to that of at least the last-but-one group of user behavior interaction information, and the influence degree of the last-but-one group of user behavior interaction information on the second user behavior interaction information is larger than that of the last-but-one group of user behavior interaction information.

In another possible implementation manner, the information processing server may also determine, in combination with the association evaluation between the plurality of first user behavior interaction information and the second user behavior interaction information, a service interaction policy of service interaction content recorded by the second user behavior interaction information. In a specific example, the information processing server obtains an arrangement position of each first user behavior interaction information in the at least two groups of user behavior interaction information, and determines a first service interaction policy of service interaction content recorded by the second user behavior interaction information according to the arrangement positions of the plurality of first user behavior interaction information and a service interaction evaluation of each service response information in the second user behavior interaction information.

In a possible implementation manner, the information processing server may receive, in real time, user behavior interaction information sent by the user operation terminal, and determine whether the currently received user behavior interaction information is second user behavior interaction information, if the currently received user behavior interaction information is the second user behavior interaction information, a first service interaction policy of the second user behavior interaction information is obtained corresponding to the manner of this step, otherwise, a second service interaction policy of the first user behavior interaction information is obtained corresponding to the manner of this step. For example, when the information processing server parses the termination signal from the currently received user behavior interaction information, the information processing server determines that the currently received user behavior interaction information is the last group of user behavior interaction information, that is, the second user behavior interaction information. It should be noted that the information processing server may determine the second user behavior interaction information or the service interaction policy of the first user behavior interaction information based on the association evaluation between the first user behavior interaction information and the second user behavior interaction information and in combination with the service interaction evaluation of the service response information in the user behavior interaction information, so that the service interaction policy of the first user behavior interaction information may represent the degree of influence of the first user behavior interaction information on the second user behavior interaction information. The more similar the first user behavior interaction information and the second user behavior interaction information are, the greater the influence on the second user behavior interaction information is, and the strategy reasonability of each user behavior interaction information and the correlation evaluation between the first user behavior interaction information and the second user behavior interaction information can be well embodied through the service interaction strategy determination mode of the step, so that the accuracy of subsequently determining the global content information is improved, and the accuracy of user behavior analysis is further improved.

S204, the information processing server determines the global content information of the second user behavior interaction information based on the policy association relationship between the first service interaction policy and the second service interaction policy.

In the embodiment of the present invention, the global content information is used to indicate the second user behavior interaction information to record the interaction integrity of the global service interaction content, where the global service interaction content is a service interaction content other than the abnormal interaction content. In the embodiment of the invention, when the matching degree difference between the first service interaction strategy and the second service interaction strategy is smaller than the target preset content matching degree, the information processing server determines that the global content information indicates the second user behavior interaction information to record the global service interaction content. When the matching degree difference between the first service interaction strategy and the second service interaction strategy is greater than the target preset content matching degree, the information processing server determines that the global content information can indicate that the second user behavior interaction information does not record the global service interaction content. The target preset content matching degree may be set based on needs, and this is not specifically limited in the embodiment of the present invention.

In a possible implementation manner, the statistical amount of the first user behavior interaction information may be multiple, the information processing server may further determine the global content information based on a key service interaction policy of the multiple first user behavior interaction information, the global content information may be in a text form, and the process may include: the information processing server determines key business interaction strategies corresponding to at least two pieces of first user behavior interaction information according to a second business interaction strategy of business service interaction contents recorded by each piece of first user behavior interaction information; the information processing server may determine, according to the key service interaction policy and the first service interaction policy, associated service interaction content of the first service interaction policy with respect to an association relationship between the first service interaction policy and the key service interaction policy, and determine the associated service interaction content as the global content information.

It should be noted that the size of the global content information represents the interaction integrity of the second user behavior interaction information including the global service interaction content, and the information processing server may continue to determine the user behavior analysis result of the target service interaction content based on the global content information through the following processes of S205 to S206.

It should be noted that S203-S204 are one possible implementation manner of the step "the information processing server determines the global content information of the second user behavior interaction information in the at least two sets of user behavior interaction information based on the service interaction policy of the service interaction content recorded by each set of user behavior interaction information", and S203-S204 are a first service interaction policy for obtaining the second user behavior interaction information and a second service interaction policy for obtaining the first user behavior interaction information, respectively, and determine the global content information based on the policy association relationship between the two service interaction policies. In another possible implementation manner, the information processing server may further obtain a first service interaction policy of the second user behavior interaction information and a third service interaction policy of the penultimate group of user behavior interaction information, and determine the global content information based on a policy association relationship between the first service interaction policy and the third service interaction policy. Of course, the embodiment of the present invention may also determine the global content information in other manners, for example, the information processing server may also determine the global content information by combining a policy association relationship between a fourth service interaction policy of the last but one group of user behavior interaction information and the first service interaction policy.

S205, when the global content information of the second user behavior interaction information meets a second target condition, the information processing server determines a user behavior analysis result of the target business service interaction content based on the first user behavior interaction information in the at least two groups of user behavior interaction information.

The second target condition includes: the global content information indicates that the second user behavior interaction information does not record global service interaction content, and the content matching degree corresponding to the global content information is smaller than at least one of the first preset content matching degrees. In one possible implementation, when the global content information satisfies the second target condition, the information processing server may directly discard the second user behavior interaction information. The information processing server can determine a user behavior analysis result corresponding to the target business service interactive content according to the user requirement matching information corresponding to the first user behavior interaction information.

S206, when the global content information of the second user behavior interaction information meets a third target condition, the information processing server determines a user behavior analysis result of the target business service interaction content based on the second user behavior interaction information and the first user behavior interaction information.

The third target condition includes: the global content information indicates that the second user behavior interaction information records global business service interaction content, and the global content information is not less than at least one of first preset content matching degrees. When the global content information meets a third target condition, the information processing server can acquire at least two service events corresponding to service interaction contents recorded by the second user behavior interaction information according to the global content information of the second user behavior interaction information; the information processing server can also determine a user behavior analysis result corresponding to the target service interaction content according to the user requirement matching information corresponding to the at least two service events and the user requirement matching information corresponding to the first user behavior interaction information.

In one possible example, the global content information records a possibility of global business service interactive content for the second user behavior interactive information; when the content matching degree corresponding to the global content information is not less than a second preset content matching degree, the information processing server may determine at least two candidate service events corresponding to the service interaction content recorded by the second user behavior interaction information as at least two service events corresponding to the second user behavior interaction information, where the second preset content matching degree is greater than the first preset content matching degree; when the content matching degree corresponding to the global content information is greater than the first preset content matching degree and less than the second preset content matching degree, the information processing server may screen, according to the global content information, candidate business service events of a third target statistical number from at least two candidate business service events corresponding to business service interaction contents recorded by the second user behavior interaction information as at least two business service events corresponding to the second user behavior interaction information. The first preset content matching degree and the second preset content matching degree may be set based on needs, which is not specifically limited in the embodiment of the present invention.

In one possible example, the screening process may include: when the content matching degree corresponding to the global content information is greater than the first preset content matching degree and less than the second preset content matching degree, the information processing server may obtain a user interest preference tag of the service response information in the second user behavior interaction information, where the user interest preference tag is used to indicate the possibility that each candidate service event is a real service event corresponding to the service interaction content recorded in the service response information; the information processing server may determine a third target statistical number of the at least two service events according to the global content information and the maximum reserved statistical number of the at least two candidate service events; the information processing server may screen out a third target statistical number of business service events from the at least two candidate business service events for which the user interest preference label satisfies a fourth target condition. For example, the third target statistical number may be 6, and the fourth target condition may be: the user interest prefers the business service events whose tags are located in the top 6 bits of the descending tag ordering.

In one possible example, the second user behavior interaction information may include a plurality of pieces of business service response information. The information processing server may obtain the user interest preference tag of each piece of business service response information in the second user behavior interaction information. The process may include: the information processing server can also identify the second user behavior interaction information as a fourth target statistical quantity of service response information according to the target information change condition and the target response state; for each piece of service response information, the information processing server can determine a service response information set where the service response information is located according to adjacent service response information of the service response information to obtain a service response information set of a first target statistical number, wherein each service response information set comprises a plurality of adjacent service response information; the information processing server may determine, according to the first target statistical number of service response information sets, a user interest preference tag of each piece of service response information in the second user behavior interaction information.

In a possible example, for each piece of business service response information in the second user behavior interaction information, the information processing server may use a business service event of each piece of business service response information in the second user behavior interaction information as a category to which the response information belongs, and use a tag of the business service event as response content status information between the categories to which the response information belongs. The information processing server acquires at least two temporary response information belonging categories of the third response information according to the category of the third response information corresponding to the previous business service response information of the business service response information, wherein each temporary response information belonging category is used for indicating a candidate business service event of the current business service response information, the information processing server obtains the labels of the at least two candidate business service events from the user interest preference labels of the current business service response information, and determining the category of the fourth response information from the categories of the at least two temporary response information according to the labels of the at least two candidate business service events, taking the category of the fourth response information as the category of the response information of the current business service response information, and taking the response content state information of the category of the fourth response information as the label corresponding to the candidate business service event. The information processing server may adjust the statistical number of the category to which the fourth response information belongs according to the size of the global content information. For example, the information processing server may obtain the maximum statistical number of categories to which the maximum response information allowed to be retained belongs, that is, the maximum statistical number of reservations of at least two candidate service events, and determine the sixth target statistical number of categories to which the fourth response information belongs according to the statistical number of categories to which the maximum response information belongs and the global content information.

For each piece of business service response information in the second user behavior interaction information, the information processing server determines the category to which the response information corresponding to the plurality of pieces of business service response information belongs and the response content state information of the category to which the response information belongs, and traverses a plurality of candidate response contents from the category to which the hot response information corresponding to the first piece of business service response information belongs to the category to which the cold response information corresponding to the last piece of business service response information belongs to the category, and takes the response content with the largest response content state information in the plurality of candidate response contents as the target response content. And the information processing server is used as at least two business service events of the second user behavior interaction information according to the business service events corresponding to the types of the response information in the target response content. When the at least two business service events meet the first target condition, the information processing server may further analyze, based on a user behavior analysis model, tags of at least two candidate user requirement matching information corresponding to the at least two business service events, and determine, according to the tags of the at least two candidate user requirement matching information, a recognition result of the second user behavior interaction information, that is, a user requirement matching information set or a single user requirement matching information corresponding to the second user behavior interaction information.

In an optional embodiment, the information processing server may further determine, according to the user requirement matching information corresponding to the at least two service events and the user requirement matching information corresponding to the first user behavior interaction information, a user behavior analysis result corresponding to the target service interaction content, which may include the content described in the following steps (1) to (4): (1) according to the user requirement matching information corresponding to the at least two business service events and the user requirement matching information corresponding to the first user behavior interaction information, performing real-time interaction action recognition on a target user behavior event in target business service interaction content to be analyzed to obtain a real-time interaction action set of the target user behavior event, wherein the real-time interaction action set comprises real-time interaction actions of a plurality of business service interaction contents; (2) acquiring target service interaction description content associated with the target service interaction content from a service interaction scene, wherein the target service interaction description content comprises: dynamic service interactive content and dynamic interactive indication information of the dynamic service interactive content; (3) determining a real-time interaction action subset from the real-time interaction action set according to the dynamic interaction indication information, and determining behavior feedback information of the real-time interaction action of each service interaction content in the real-time interaction action subset on the service interaction content of the target service interaction content; (4) and determining a dynamic behavior portrait for the dynamic business service interactive content according to the behavior feedback information of the real-time interactive action of each business service interactive content in the business service interactive content of the target business service interactive content, and determining a user behavior analysis result corresponding to the target business service interactive content according to the dynamic behavior portrait. By the design, the interaction action can be analyzed, so that the corresponding dynamic behavior portrait is determined, and when the user behavior analysis result corresponding to the target business service interaction content is determined according to the dynamic behavior portrait, the relevance among the user behavior, the user intention and the actual business can be considered, so that the efficiency of determining the user behavior analysis result is improved. Based on this, the aforementioned step "determining a dynamic behavior representation for the dynamic service interaction content according to the behavior feedback information of the service interaction content of the real-time interaction action of each service interaction content, and determining a user behavior analysis result corresponding to the target service interaction content according to the dynamic behavior representation" may further include: determining a local dynamic behavior portrait aiming at the dynamic business service interactive content according to the dynamic behavior intention characteristics of the target business interactive description content corresponding to the dynamic business service interactive content, wherein the local dynamic behavior portrait comprises a business requirement behavior portrait or a business output behavior portrait, or the local dynamic behavior portrait comprises the business requirement behavior portrait and the business output behavior portrait; behavior feedback information of business service interactive contents of key behavior intention characteristics in the target business service interactive contents is obtained, wherein the key behavior intention characteristics are determined according to each real-time interactive action in the real-time interactive action subset; and taking behavior feedback information of the business service interactive content with the key behavior intention characteristics in the target business service interactive content as a behavior portrait corresponding to dynamic behavior feedback information, and determining a user behavior analysis result corresponding to the target business service interactive content according to the behavior portrait corresponding to the dynamic behavior feedback information and the local dynamic behavior portrait. By the design, the local dynamic behavior portrait is split and analyzed, so that a user behavior analysis result can be accurately determined. For some optional embodiments, the step of determining a dynamic behavior representation for the dynamic service interaction content according to the behavior feedback information of the service interaction content of the target service interaction content of the real-time interaction action of each service interaction content, and determining a user behavior analysis result corresponding to the target service interaction content according to the dynamic behavior representation may include the following contents: determining a plurality of key behavior intention characteristics from the real-time interaction action subset, and determining behavior feedback information of the business service interaction content of the plurality of key behavior intention characteristics in the target business service interaction content; behavior feedback information of the service interaction content with the determined multiple key behavior intention characteristics is used as a behavior portrait corresponding to the dynamic behavior feedback information, and a user behavior analysis result corresponding to the target service interaction content is determined according to the behavior portrait corresponding to the dynamic behavior feedback information; wherein a plurality of dynamic behavior intention characteristics are indicated in the target business interaction description content, and behavior feedback information of the plurality of dynamic behavior intention characteristics in the target business service interaction content is determined according to a behavior portrait corresponding to the dynamic behavior feedback information.

In one possible example, for example, assuming that the number of categories to which active response information corresponding to the xth service response information in the second user behavior interaction information belongs is m, the category determining process to which response information corresponding to x +1 pieces of response information belongs may be: the information processing server traverses the category to which the temporary response information of each category to which the active response information belongs in the categories to which the m active response information belongs, marks the category to which the temporary response information of each category to which the active response information belongs, and if the number of the marked categories to which the temporary response information belongs is k, the information processing server can sort the categories to which the k response information belongs on the basis of a preset category screening algorithm and on the basis of the maximum allowable statistical quantity, namely, the upper limit of the category to which the active response information allowed to be discarded belongs is p, selects the first u response information to be reserved, and deletes (discards) the categories to which the other response information belongs.

It should be noted that the information processing server may filter and discard categories to which the response information of the user behavior interaction information belongs based on the global content information, so as to reduce the number of categories to which the active response information belongs, reduce the operating pressure of the server, and improve the efficiency of identifying and returning results. In addition, a business interaction strategy of business service interaction content recorded by the second user behavior interaction information is also considered, and the recognition result is ensured not to be influenced by the discarding process of the class to which the response information belongs, so that on the premise of ensuring accurate recognition, the time consumed by response of user behavior analysis is reduced, and the recognition efficiency of user behavior analysis is improved.

In a possible example, to describe the above processes of S201 to S206 in more detail, in another example, the following describes the overall process of the embodiment of the present invention, and takes the process of analyzing the user behavior by information interaction between the information processing server and the user operation terminal as an example, when the user operation terminal collects the service response information, the target response information amount of the user behavior interaction information may be dynamically calculated, the service response information is included according to the target response information amount, the included user behavior interaction information is sent to the information processing server in real time, the information processing server receives the user behavior interaction information uploaded by the user operation terminal in real time, the statistical number of the user behavior interaction information is multiple, the information processing server decompresses each group of user behavior interaction information, and determines whether the currently received response information is the second user behavior interaction information, that is, the last set of user behavior interaction information. For each first user behavior interaction information, namely, the user behavior interaction information except the last group of user behavior interaction information, the information processing server can acquire a service interaction strategy of the first user behavior interaction information, and perform user behavior analysis on the first user behavior interaction information through processes of splitting processing, user interest intention extraction, user interest preference labels, response content expansion and the like, so as to determine user requirement matching information corresponding to each first user behavior interaction information. For the second user behavior interaction information, the information processing server obtains the global content information of the second user behavior interaction information based on the service interaction strategy of the first user behavior interaction information and the service interaction strategy of the second user behavior interaction information, and according to the global content information, the information processing server determines the user behavior analysis result of the target service interaction content based on the first user behavior interaction information or the second user behavior interaction information and the first user behavior interaction information in the at least two groups of user behavior interaction information, so that the efficiency of the user behavior analysis is ensured on the premise that the identification result of the target service interaction content is accurately analyzed.

In the embodiment of the invention, the global content information of the second user behavior interaction information is determined through the service interaction strategy of the service interaction content recorded by each group of user behavior interaction information, the interaction integrity of the second user behavior interaction information recording global service interaction content is obtained based on the global content information, and when the global content information meets a second target condition, the user behavior analysis is carried out only based on the first user behavior interaction information, so that the number of the user behavior interaction information participating in the user behavior analysis is reduced, and the time consumed by information processing is reduced; and the user behavior analysis is carried out based on the global content information, so that the problems of inaccurate identification and low reliability caused by directly deleting the second user behavior interaction information are avoided, and the efficiency of the user behavior analysis is improved on the premise of ensuring the accuracy of the user behavior analysis.

In some optional embodiments, a method for analyzing user behavior in combination with big data is further provided, where an execution subject of an embodiment of the present invention is an information processing server, and the method includes:

s301, the information processing server obtains at least two groups of user behavior interaction information, and the at least two groups of user behavior interaction information are used for recording the interaction content of the target business service.

In the embodiment of the present invention, the target service interaction content may be a service interaction content obtained when a user interacts with a service, and the at least two sets of user behavior interaction information include service response information corresponding to the target service interaction content. The implementation of this step is a process similar to the above S201, and is not described in detail here.

S302, the information processing server determines the global content information of the second user behavior interaction information in the at least two groups of user behavior interaction information based on the service interaction strategy of the service interaction content recorded by each group of user behavior interaction information.

In the embodiment of the present invention, the second user behavior interaction information is a last group of user behavior interaction information in the at least two groups of user behavior interaction information, the global content information is used to indicate the interaction integrity of the second user behavior interaction information recording global service interaction content, and the global service interaction content refers to service interaction content except for abnormal interaction content. In a possible implementation manner, the information processing server may determine, based on the service interaction evaluation of each piece of service response information included in the second user behavior interaction information and the first user behavior interaction information, a first service interaction policy of service interaction content recorded in the second user behavior interaction information and a second service interaction policy of service interaction content recorded in the first user behavior interaction information. The information processing server may determine global content information of the second user behavior interaction information based on a policy association relationship between the first service interaction policy and the second service interaction policy. The implementation of this step is the same as the process of S203-S204, and is not described herein again.

S303, when the global content information of the second user behavior interaction information meets a second target condition, the information processing server determines a user behavior analysis result of the target service interaction content based on the first user behavior interaction information in the at least two groups of user behavior interaction information.

In the embodiment of the present invention, the first user behavior interaction information is user behavior interaction information other than the last group of user behavior interaction information in the at least two groups of user behavior interaction information. The second target condition includes: the global content information indicates that the second user behavior interaction information does not record global service interaction content, and the content matching degree corresponding to the global content information is smaller than at least one of the first preset content matching degrees. In one possible implementation, when the global content information satisfies the second target condition, the information processing server may directly discard the second user behavior interaction information. The information processing server can determine a user behavior analysis result corresponding to the target business service interactive content according to the user requirement matching information corresponding to the first user behavior interaction information. In another possible implementation manner, when the global content information of the second user behavior interaction information satisfies a third target condition, the information processing server determines a user behavior analysis result of the target service interaction content based on the second user behavior interaction information and the first user behavior interaction information. The third target condition includes: the global content information indicates the second user behavior interaction information to record global business service interaction content, and the content matching degree corresponding to the global content information is not less than at least one of first preset content matching degrees. When the global content information meets a third target condition, the information processing server can acquire at least two service events corresponding to service interaction contents recorded by the second user behavior interaction information according to the global content information of the second user behavior interaction information; the information processing server can also determine a user behavior analysis result corresponding to the target service interaction content according to the user requirement matching information corresponding to the at least two service events and the user requirement matching information corresponding to the first user behavior interaction information. The implementation of this step is the same as the process of S205-S206, and is not described herein again.

In the embodiment of the invention, the global content information of the second user behavior interaction information is determined through the service interaction strategy of the service interaction content recorded by each group of user behavior interaction information, the interaction integrity of the second user behavior interaction information recording global service interaction content is obtained based on the global content information, and when the global content information meets a second target condition, the user behavior analysis is carried out only based on the first user behavior interaction information, so that the number of the user behavior interaction information participating in the user behavior analysis is reduced, and the time consumed by information analysis is reduced; and the user behavior analysis is carried out based on the global content information, so that the problems of inaccurate identification and low reliability caused by directly deleting the second user behavior interaction information are avoided, and the efficiency of the user behavior analysis is improved on the premise of ensuring the accuracy of the user behavior analysis.

On the basis, please refer to fig. 3, the present invention further provides a block diagram of a user behavior analysis apparatus 300 combining big data, which includes the following functional modules.

The information obtaining module 310 is configured to obtain user behavior interaction information, perform service response information identification on the user behavior interaction information, and perform user interest intention analysis on the obtained service response information to obtain a user interest preference tag of the service response information; and the user behavior interaction information is used for recording the interaction content of the target business service.

A requirement determining module 320, configured to determine, according to the user interest preference tag, user requirement matching information or a user requirement matching information set corresponding to the service response information.

And the behavior analysis module 330 is configured to determine a user behavior analysis result corresponding to the target service interaction content according to the user requirement matching information or the user requirement matching information set.

The method embodiments provided by the embodiments of the present application may be executed in an information processing server, a computer device, or a similar computing device. Taking the example of running on an information processing server, fig. 4 is a hardware structure block diagram of an information processing server implementing a user behavior analysis method combined with big data according to an embodiment of the present invention. As shown in fig. 4, the information processing server 101 may include one or more (only one is shown in fig. 4) processors 102 (the processors 102 may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, and optionally, may further include a transmission device 106 for communication functions. It will be understood by those skilled in the art that the structure shown in fig. 4 is merely an illustration, and does not limit the structure of the information processing server. For example, the information processing server 101 may also include more or fewer components than those shown in fig. 4, or have a different configuration than that shown in fig. 4.

The memory 104 may be used to store a computer program, for example, a software program and a module of application software, such as a computer program corresponding to a user behavior analysis method combined with big data in an embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely disposed from the processor 102, and these remote memories may be connected to the information processing server 101 through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission device 106 is used for receiving or transmitting data via a network. The above-described concrete examples of the network may include a wireless network provided by a communication provider of the information processing server 101. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.

Further, a readable storage medium is provided, on which a program is stored, which when executed by a processor implements the method described above.

It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.

Claims

1. A method for analyzing user behavior in combination with big data, the method comprising:

acquiring user behavior interaction information, performing service response information identification on the user behavior interaction information, and performing user interest intention analysis on the acquired service response information to obtain a user interest preference tag of the service response information; the user behavior interaction information is used for recording the interaction content of the target business service;

determining user requirement matching information or a user requirement matching information set corresponding to the business service response information according to the user interest preference label;

and determining a user behavior analysis result corresponding to the target business service interactive content according to the user requirement matching information or the user requirement matching information set.

2. The method according to claim 1, wherein user behavior interaction information is acquired, business service response information identification is performed on the user behavior interaction information, and user interest intention analysis is performed on the acquired business service response information to obtain a user interest preference tag of the business service response information; the user behavior interaction information is used for recording the interaction content of the target business service, and comprises the following steps:

acquiring at least two groups of user behavior interaction information, wherein the at least two groups of user behavior interaction information are used for recording the interaction content of the target business service;

identifying service response information of first user behavior interaction information in the at least two groups of user behavior interaction information to obtain a plurality of pieces of service response information, wherein the first user behavior interaction information is user behavior interaction information except the last group of user behavior interaction information in the at least two groups of user behavior interaction information;

extracting the interest intention of the user from each piece of business service response information to obtain the interest intention of the user of each piece of business service response information;

acquiring business service response information sets of a first target statistic quantity according to the first target statistic quantity and a second target statistic quantity, wherein the first target statistic quantity is used for indicating the statistic quantity of the business service response information sets corresponding to the one-time user interest preference tag determination process;

and determining a user interest preference label of each piece of business service response information based on the user interest intention of each business service response information set in the first target statistical number of business service response information sets.

3. The method according to claim 2, wherein determining the user requirement matching information or the user requirement matching information set corresponding to the business service response information according to the user interest preference tag comprises:

determining a business service event of each piece of business service response information according to the user interest preference label of each piece of business service response information;

determining user requirement matching information or a user requirement matching information set corresponding to the plurality of pieces of business service response information according to at least two business service events of the plurality of pieces of business service response information;

determining a user behavior analysis result corresponding to the target business service interaction content according to the user requirement matching information or the user requirement matching information set, wherein the user behavior analysis result comprises the following steps:

and determining a user behavior analysis result corresponding to the target service interaction content according to the user requirement matching information corresponding to the first user behavior interaction information.

4. The method of claim 3, wherein the determining the business service event of each piece of business service response information according to the user interest preference tag of each piece of business service response information comprises:

for each piece of business service response information, according to the user interest preference label of each piece of business service response information, screening out the candidate business service event corresponding to the maximum label attribute value from at least two candidate business service events of each piece of business service response information as the business service event of each piece of business service response information, wherein the user interest preference label of each piece of business service response information comprises at least two corresponding candidate business service events and the label of each candidate business service event.

5. The method according to claim 3, wherein the determining, according to at least two service events of the service response messages, user requirement matching information or a user requirement matching information set corresponding to the service response messages comprises:

determining the types of the response information corresponding to the plurality of pieces of business service response information and the response content state information of the types of the response information;

traversing from the category to which the hot response information corresponding to the first service response information belongs to the category until the category to which the cold response information corresponding to the last service response information belongs to the response content state information of the category to which the response information belongs to obtain a plurality of candidate response contents;

updating the most frequent response content of the state information of the response contents in the candidate response contents as target response content;

according to the business service events corresponding to the categories of the response information in the target response content, at least two business service events of the first user behavior interaction information are used;

when the at least two business service events meet a first target condition, analyzing labels of at least two candidate user requirement matching information corresponding to the at least two business service events based on a user behavior analysis model, wherein the first target condition is a business service quality monitoring condition corresponding to the at least two business service events;

and determining user requirement matching information or a user requirement matching information set corresponding to the plurality of pieces of business service response information according to the labels of the at least two candidate user requirement matching information.

6. The method according to claim 5, wherein the determining the category to which the response information corresponding to the plurality of pieces of business service response information belongs and the response content status information of the category to which the response information belongs comprises:

for each piece of service response information, obtaining at least two categories to which the first response information belongs according to the category to which the first response information corresponding to the previous piece of service response information of each piece of service response information belongs, wherein the category to which each piece of temporary response information belongs is used for indicating a candidate service event of each piece of service response information;

obtaining a label of each candidate business service event from the user interest preference label of each piece of business service response information;

determining the category of the second response information from the categories of the at least two pieces of temporary response information according to the label of each candidate business service event;

and taking the category to which the second response information belongs as the category to which the response information of each piece of business service response information belongs, wherein the response content state information of the category to which the second response information belongs is a label corresponding to the candidate business service event.

7. The method according to claim 3, wherein before determining the user behavior analysis result corresponding to the target service interaction content according to the user requirement matching information corresponding to the first user behavior interaction information, the method further comprises:

determining global content information of second user behavior interaction information in the at least two groups of user behavior interaction information based on a service interaction strategy of service interaction content recorded by each group of user behavior interaction information, wherein the global content information is used for indicating the interaction integrity of the second user behavior interaction information recording global service interaction content, the global service interaction content refers to service interaction content except abnormal interaction content, and the second user behavior interaction information is the last group of user behavior interaction information in the at least two groups of user behavior interaction information;

the determining, according to the user requirement matching information corresponding to the first user behavior interaction information, a user behavior analysis result corresponding to the target service interaction content includes: when the global content information of the second user behavior interaction information meets a second target condition, determining a user behavior analysis result corresponding to the target service interaction content according to user requirement matching information corresponding to the first user behavior interaction information; wherein the second target condition comprises: the global content information indicates that the second user behavior interaction information does not record global service interaction content, and the content matching degree corresponding to the global content information is smaller than at least one of first preset content matching degrees;

the determining, based on the service interaction policy of the service interaction content recorded by each set of user behavior interaction information, global content information of second user behavior interaction information in the at least two sets of user behavior interaction information includes:

determining a first business interaction strategy of business service interaction content recorded by the second user behavior interaction information and a second business interaction strategy of business service interaction content recorded by the first user behavior interaction information based on business interaction evaluation of each piece of business service response information included by the second user behavior interaction information and the first user behavior interaction information;

determining global content information of the second user behavior interaction information based on a policy association relationship between the first service interaction policy and the second service interaction policy;

the determining, based on the service interaction evaluation of each piece of service response information included in the second user behavior interaction information and the first user behavior interaction information, a first service interaction policy of service interaction content recorded in the second user behavior interaction information and a second service interaction policy of service interaction content recorded in the first user behavior interaction information includes:

for the second user behavior interaction information, acquiring a first service interaction strategy of service interaction content recorded by the second user behavior interaction information according to the service interaction evaluation of each piece of service response information in the second user behavior interaction information;

and for each piece of first user behavior interaction information, acquiring a second service interaction strategy of service interaction content recorded by the first user behavior interaction information according to the association evaluation between the first user behavior interaction information and the second user behavior interaction information and the service interaction evaluation of each piece of service response information in the first user behavior interaction information, wherein the association evaluation is used for indicating the influence degree of the service interaction evaluation of a service item in the first user behavior interaction information on the service interaction evaluation of the service response information in the second user behavior interaction information.

8. The method of claim 7, wherein the determining the global content information of the second user behavior interaction information based on the policy association relationship between the first service interaction policy and the second service interaction policy comprises:

determining key business interaction strategies corresponding to at least two pieces of first user behavior interaction information according to a second business interaction strategy of business service interaction contents recorded by each piece of first user behavior interaction information;

and determining the associated service interaction content of the first service interaction strategy relative to the association relation between the first service interaction strategy and the key service interaction strategy according to the key service interaction strategy and the first service interaction strategy, and determining the associated service interaction content as the global content information.

9. The method according to claim 7, wherein the determining, according to the user requirement matching information corresponding to the first user behavior interaction information, a user behavior analysis result corresponding to the target service interaction content comprises:

when the global content information of the second user behavior interaction information meets a third target condition, acquiring at least two service events corresponding to service interaction content recorded by the second user behavior interaction information according to the global content information of the second user behavior interaction information;

determining a user behavior analysis result corresponding to the target service interaction content according to the user requirement matching information corresponding to the at least two service events and the user requirement matching information corresponding to the first user behavior interaction information; wherein the third target condition comprises: the global content information indicates that the second user behavior interaction information records global business service interaction content, and the content matching degree corresponding to the global content information is not less than at least one of first preset content matching degrees.

10. An information processing server, comprising a processor and a memory; the processor is connected in communication with the memory, and the processor is configured to read the computer program from the memory and execute the computer program to implement the method of any one of claims 1 to 9.