CN111131388A

CN111131388A - User behavior path analysis method and device, electronic equipment and storage medium

Info

Publication number: CN111131388A
Application number: CN201911164401.XA
Authority: CN
Inventors: 林奇亮; 梁新敏; 陈羲
Original assignee: Shanghai Fengzhi Technology Co Ltd
Current assignee: Shanghai Fengzhi Technology Co Ltd
Priority date: 2019-11-25
Filing date: 2019-11-25
Publication date: 2020-05-08

Abstract

According to the user behavior path analysis method and device, the electronic device and the storage medium, different behaviors of each user are defined through the obtained access log, different behaviors are marked by using the behavior marks, behavior classification is carried out according to the behavior marks, the user ID and the behavior time, at least one behavior class of the user is obtained, the behavior classes are divided according to the behavior time included in the behavior classes, and at least one continuous behavior of each user is obtained. By the method, the continuous behaviors of each user at the client or the website can be collected and analyzed, so that the client or the website can be optimized according to the behaviors of the user.

Description

User behavior path analysis method and device, electronic equipment and storage medium

Technical Field

The present application relates to the field of data processing technologies, and in particular, to a user behavior path analysis method and apparatus, an electronic device, and a storage medium.

Background

In the prior art, user behavior analysis refers to statistics and analysis of related data under the condition of obtaining basic data of website (or applet) access amount, and finds out the rule of the website (or applet) accessed by a user. There are many methods for analyzing user behavior in big data scene, and user path calculation and analysis is a method for analyzing user behavior.

The path calculation analysis refers to analysis of a path of a user, and analyzes user behavior by collecting data of a relevant path operated when the user uses a service and analyzing the data to obtain an analysis result.

Disclosure of Invention

In view of the above, an object of the present application is to provide a user behavior path analysis method, apparatus, electronic device and storage medium.

In a first aspect, an embodiment provides a user behavior path analysis method applied to an electronic device, where the method includes:

defining user behaviors of each user according to the acquired access log, defining different behaviors according to at least one of different behavior names, behavior descriptions and application program IDs in the access log, and marking different behaviors by using behavior identifiers;

performing behavior classification according to the behavior identification and the user ID and the behavior time in the access log to obtain at least one behavior class, so that each behavior class comprises the behavior time, the behavior identification and the user ID corresponding to each user;

and dividing the behavior categories according to the difference value between the behavior time included in each behavior category to obtain at least one continuous behavior of each user, wherein the continuous behavior at least comprises one behavior category.

In an alternative embodiment, dividing the behavior categories according to a difference between behavior times included in the behavior categories to obtain at least one continuous behavior of each user includes:

sorting each behavior category according to the behavior time included in the behavior category;

judging whether the difference value of the behavior time between each behavior category and the previous behavior category exceeds a preset value, if not, marking the behavior category by using a first mark, and if so, marking the behavior category by using a second mark;

and dividing the behavior categories according to the marks of the behavior categories to obtain at least one continuous behavior of each user.

In an alternative embodiment, the dividing the behavior categories according to the labels of the behavior categories to obtain at least one continuous behavior of each user includes:

accumulating the marks of each behavior category according to the sequencing sequence of each behavior category, and recording the accumulation result of each behavior category;

and dividing the behavior categories with the same accumulation result into a continuous behavior.

In an alternative embodiment, after dividing the behavior categories according to a difference between behavior times included in the behavior categories to obtain at least one continuous behavior of each user, the method further includes:

and dividing the behavior categories included in at least one continuous behavior into different hierarchies according to the sequence of the behavior time, and identifying the different hierarchies by using hierarchy identification, wherein each hierarchy includes one behavior category.

In an optional implementation manner, after dividing the behavior categories included in at least one of the continuous behaviors into different hierarchies according to the sequence of the behavior time and identifying the different hierarchies by using hierarchy identifiers, the method further includes:

and drawing a user path graph according to the hierarchy identification in the continuous behaviors.

In an optional implementation manner, before defining the user behavior of each user according to the obtained access log, the method further includes:

and obtaining the access log of each user from the client or the server of the website.

In a second aspect, an embodiment provides a user behavior path analysis apparatus, which is applied to an electronic device, and the apparatus includes:

the behavior definition module is used for defining the user behavior of each user according to the obtained access log, defining different behaviors according to at least one of different behavior names, behavior descriptions and application program IDs in the access log, and marking the different behaviors by using behavior identifiers;

a behavior classification module, configured to perform behavior classification according to the behavior identifier and the user ID and behavior time in the access log to obtain at least one behavior class, so that each behavior class includes the behavior time, the behavior identifier, and the user ID corresponding to each user;

and the behavior classification module is used for classifying the behavior classes according to the difference value between the behavior time included in each behavior class so as to obtain at least one continuous behavior of each user, wherein the continuous behavior at least comprises one behavior class.

In an alternative embodiment, the apparatus further comprises:

and the hierarchy dividing module is used for dividing the behavior categories included in at least one continuous behavior into different hierarchies according to the sequence of the behavior time and identifying the different hierarchies by using hierarchy identification, wherein each hierarchy includes one behavior category.

In a third aspect, an embodiment provides an electronic device, including a processor and a non-volatile memory storing computer instructions, where the computer instructions, when executed by the processor, cause the electronic device to perform the user behavior path analysis method according to any one of the foregoing embodiments.

In a fourth aspect, an embodiment provides a storage medium, in which a computer program is stored, and the computer program, when executed, implements the user behavior path analysis method according to any one of the foregoing embodiments.

The beneficial effect of this application:

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;

fig. 2 is a flowchart of a user behavior path analysis method according to an embodiment of the present disclosure;

FIG. 3 is a flowchart illustrating sub-steps of step S230 in FIG. 2;

fig. 4 is a second flowchart of a user behavior path analysis method according to an embodiment of the present application;

fig. 5 is a functional block diagram of a user behavior path analysis apparatus according to an embodiment of the present application.

Description of the main element symbols: 100-an electronic device; 110-user behavior path analysis means; 120-a memory; 130-a processor; 1101-a behavior definition module; 1102-a behavior classification module; 1103-a behavior partitioning module; 1104-hierarchical partitioning module.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.

Referring to fig. 1, fig. 1 is a schematic structural diagram of an electronic device 100 according to an embodiment of the present disclosure. The electronic device 100 includes a processor 130, a memory 120, and a user behavior path analysis apparatus 110, where the memory 120 and the elements of the processor 130 are directly or indirectly electrically connected to each other to implement data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The user behavior path analysis device 110 includes at least one software function module which can be stored in the memory 120 in the form of software or firmware (firmware) or is fixed in an Operating System (OS) of the electronic device 100. The processor 130 is used for executing executable modules stored in the memory 120, such as software functional modules and computer programs included in the user behavior path analysis device 110.

The Memory 120 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 120 is used for storing a program, and the processor 130 executes the program after receiving the execution instruction.

The processor 130 may be an integrated circuit chip having signal processing capabilities. The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

Referring to fig. 2, fig. 2 is a flowchart of a user behavior path analysis method according to an embodiment of the present disclosure. The method is applied to the electronic device 100 in fig. 1, and is used for analyzing the behavior path of each user. The method comprises the following steps:

step S210, defining the user behavior of each user according to the obtained access log, defining different behaviors according to at least one of different behavior names, behavior descriptions and application program IDs in the access log, and marking different behaviors by using behavior identifications.

Step S220, performing behavior classification according to the behavior identification and the user ID and the behavior time in the access log to obtain at least one behavior class, so that each behavior class comprises the behavior time, the behavior identification and the user ID corresponding to each user.

Step S230, the behavior categories are divided according to the difference between the behavior times included in the behavior categories to obtain at least one continuous behavior of each user. Wherein the continuous behavior comprises at least one behavior category.

Through the steps, the behaviors of the user at different time points can be acquired from the access log, and the behaviors of each user at different time points can be acquired by analyzing the data such as the behavior name, the behavior description, the application program ID, the behavior time, the user ID and the like acquired from the access log, so that the behaviors of the user can be analyzed.

For example, in an applet, it is a user path that a user opens the applet, the user clicks on an item, the user joins a car purchase, and the user purchases payment. By analyzing the user path, the design of the applet can be optimized, so that the user can click more on the applet.

The above steps are exemplified by path analysis in a small program. Generally, the contents of the user ID, the application ID, the behavior type, the behavior description, and the time when the behavior occurs can be generally obtained from the access log.

The application program ID refers to the content contained in the appID field in the access log and is used for representing different application applets; the behavior type refers to the content contained in the eventName field in the access log and is used for representing the behavior type of the user, such as behaviors of clicking, logging in, closing a page and the like; the behavior description refers to content contained in an eventDesc field in an access log, and is used for performing supplementary description on behaviors of the user, for example, a specific page clicked, a title of the page, a shared page or a name of a participating activity.

When at least one of the application ID, the behavior type, and the behavior description is different, the behavior can be regarded as different behavior, that is, the behavior can be defined as a combination of appID, eventName, and eventdescr fields. Not all behaviors include the application id (appid), the behavior type (eventName), and the behavior description (eventDesc), and a behavior may include only at least one of them or a combination of any two of them.

After defining the different behaviors, the different behaviors also need to be marked using behavior identification. Optionally, the action field may be used to represent different behaviors, where the content contained in the action field is a set of contents contained in the appID field, the eventName field, and the eventdescr field in the access log. For example, the content in the action field may be content of app1_ page _ layer or app2_ appshoot, where app1 and app2 are content contained in the appID field and respectively represent the first applet and the second applet; page and applaunch are the contents contained in the eventName field, representing page and app login, respectively; shouye is the content contained in the eventDesc field for indicating the top page of the current page.

Different behaviors of the user can be uniquely marked through the behavior identification, so that the behavior identification corresponds to the different behaviors of the user one by one. After the behavior identifier is obtained, the behavior needs to be classified according to the user ID and the behavior time.

The user ID is a unique identification of the user identity, and generally refers to the content contained in the ID field in the access log, and the behavior time refers to the time of the user operating the applet and generally refers to the content contained in the time field in the access log.

After the behaviors of the users are defined and classified, the behaviors of the users at various time points can be obtained, and each behavior class comprises a user ID, a behavior identifier and behavior time and is used for representing the behaviors of the users at various time points.

For example, a user ID included in a behavior category may be 1234, a behavior identifier may be app1_ page _ shouye, and a behavior time may be 11 months and 20 days in 2019, 12 points and 20 minutes and 30 seconds. Of course, the above data is only an illustration of the behavior category, and does not constitute a limitation on the behavior category.

Since the access log is typically a monitoring of the user's access during a period of time, the user may have continued to operate on an applet during the period of time. Therefore, in order to obtain the behaviors of the continuous operation of the user, the multiple behavior categories of the user need to be divided according to the behavior time, so as to obtain at least one continuous behavior of the user. In general, a behavior class in which a behavior time between two behavior classes does not exceed a preset value may be regarded as a behavior class in one continuous behavior.

For example, it is assumed that the preset value is 30 minutes, that is, the interval time of the action time does not exceed 30 minutes, and the same continuous action can be considered. If the first action1 of the user 1234 is 09 o ' clock 20 min 35 sec at 11/20 th day 2019, the second action2 of the user 1234 is 09 o ' clock 21 min 50 sec at 11/20 th day 2019, and the third action2 of the user 1234 is 18 o ' clock 22 min 50 sec at 11/20 th day 2019. The first action1 of user 1234 may be divided into one continuous action with its second action2 and the third action3 may be one of the other continuous actions.

At least one continuous behavior of each user can be obtained through the steps, and the continuous behavior is used for representing one continuous behavior path of the user.

It is understood that 30 minutes is only an example of the preset value, and in other embodiments, the preset value may also be 10 minutes, 20 minutes or 40 minutes, which is not limited herein.

Referring to fig. 3, fig. 3 is a flowchart illustrating sub-steps of step S230 in fig. 2. Step S230 includes the following substeps:

sub-step S2301, sorting each behavior class according to the behavior time included in the behavior class.

And the substep S2302 is used for judging whether the difference value of the behavior time between each behavior type and the adjacent behavior type exceeds a preset value, if not, marking the behavior type by using a first mark, and if so, marking the behavior type by using a second mark.

In the above steps, each behavior category includes a user ID, a behavior identifier, and a behavior time. Each user may have a plurality of behavior categories within a period of time, the plurality of behavior categories of the same user are sorted according to the behavior time of each behavior category, whether the difference value between the behavior time of each behavior category and the behavior time of the previous behavior category exceeds a preset value (for example, 30 minutes) is judged, if not, the behavior category is marked as a first mark, and if, the behavior category exceeds 30 minutes, the behavior type is marked as a second mark. The tempID field may be used to indicate the flags of the behavior classes, where the first flag may be 0, the second flag may be 1, and the first behavior type after sorting may be marked null because there is no previous behavior type.

For example, referring to table 1, table 1 is an illustration of the ordering and labeling of each behavior type.

ID	action	time	tempID
				1234	app1_page_shouye	2019-10-19 13:30:00	null
1234	app1_clickitem	2019-10-19 13:31:00	0
				1234	app1_close	2019-10-19 13:32:00	0
1234	app2_launch	2019-10-19 18:00:00	1
				1234	app2_close	2019-10-19 18:01:00	0

In table 1, ID represents user ID, action represents different behavior categories of the user, time represents behavior time, and tempID represents a mark of the behavior category. The first behavior category is labeled null, the behavior time difference between the second behavior category and the third behavior category and the previous behavior category does not exceed the preset value (30 minutes), so the second behavior category and the third behavior category are labeled 0, the behavior time difference between the fourth behavior category and the previous behavior category exceeds the preset value (30 minutes), so the fourth behavior category is labeled 1, the behavior time difference between the fifth behavior category and the fourth behavior category does not exceed the preset value (30 minutes), so the fifth behavior category is labeled 0.

After sub-step S2302, step S230 further includes:

and a substep S2303 of dividing each behavior category according to the marks of the behavior categories to obtain at least one continuous behavior of each user.

Specifically, in sub-step S2303, the labels of each behavior category are accumulated according to the sorting order of each behavior category, and the accumulated result of each behavior category is recorded; and dividing the behavior categories with the same accumulation result into a continuous behavior.

In this step, the accumulated result of each behavior type may be represented using the cusumID field, for example, please refer to Table 2, where Table 1 is an illustration of the sorting, labeling, and accumulated result for each behavior type.

ID	action	time	tempID	cusumID
					1234	app1_page_shouye	2019-10-19 13:30:00	null	null
1234	app1_clickitem	2019-10-19 13:31:00	0	0
					1234	app1_close	2019-10-19 13:32:00	0	0
1234	app2_launch	2019-10-19 18:00:00	1	1
					1234	app2_close	2019-10-19 18:01:00	0	1

In table 2, ID represents a user ID, action represents a behavior category, time represents a behavior time, and the value in the accumulation result cusumID of each behavior category is the sum of the values in tempids of all the behavior categories preceding the behavior category. When the continuous behavior division is performed, the behavior categories with the same value in the cusumID are divided into one continuous behavior. In table 2, the value in the cusumID of the first behavior type is null, and the values in the cusumids of the second and third behavior types are 0, so that a continuous behavior can be classified, and the behavior time difference between the first behavior type and the second behavior type does not exceed the preset value (30 minutes), so that the first behavior type, the second behavior type, and the third behavior type can also be classified as a continuous behavior; the value in cusumID of the fourth and fifth behavior categories is 1, divided into another consecutive behavior.

Referring to fig. 4, fig. 4 is a second flowchart of a user behavior path analysis method according to an embodiment of the present application. After step S230, the user behavior path analysis method further includes:

step S240, dividing the behavior categories included in the at least one continuous behavior into different hierarchies according to the sequence of the behavior time, and identifying the different hierarchies by using the hierarchy identifier. Wherein each hierarchy includes a behavior category.

In this step, each continuous behavior at least includes one behavior category, and when one continuous behavior includes a plurality of behavior categories, the plurality of behavior types in one continuous behavior are hierarchically divided according to the behavior time included in each behavior category, and different hierarchies are identified by using hierarchy identification. Level fields may be used to represent the level identifiers, for example, the content in the level field of the behavior type corresponding to the first level in one continuous behavior may be 1, that is, 1 in the level field is the level identifier of the first level. Thus, all behavior types in one continuous behavior can be hierarchically divided, and different hierarchies can be identified by using hierarchical identification.

Referring to fig. 4, optionally, after step S240, the user behavior path analysis method further includes:

and step S250, drawing a user path graph according to the hierarchy identification in the continuous behaviors.

In this step, each continuous behavior may include multiple behavior categories or one behavior category. When there are multiple behavior categories, for example, three behavior categories with hierarchical identifiers of 1, 2, and 3 are included in the continuous behavior session 1.

When the user path graph is drawn, the arrows are used to draw the front and back sequence of the three behavior categories in the session1 according to the sequence of the hierarchy identifiers 1, 2 and 3, so that the path graph of the session1 is obtained.

According to the method, the path diagram can be drawn for a plurality of continuous behaviors of the same user, so that a plurality of path diagrams of the user are obtained, and the path of the user during browsing or operating the small program can be known by analyzing the path diagrams, so that a programmer can optimize the small program according to the behavior path of the user.

Optionally, in this embodiment, before step S210, the method further includes: and obtaining the access log of each user from the client or the server of the website.

In this step, the access log of each user in a certain period of time may be obtained from the client or website of each application. When obtaining the access log from the website, the programmer may analyze the behavior path of the user according to the access log obtained through the website so as to optimize the website. When the access log is acquired from the client, the programmer can analyze the behavior path of the user according to the access log acquired through the client so as to optimize the client. Or acquiring a log of accesses of users to different applets from a certain client (e.g. a WeChat client) so as to optimize the applets.

Referring to fig. 5, fig. 5 is a functional block diagram of a user behavior path analysis apparatus 110 according to an embodiment of the present application, where the apparatus is applied to an electronic device 100, and the user behavior path analysis apparatus 110 includes:

the behavior definition module 1101 is configured to define a user behavior of each user according to the obtained access log, define different behaviors according to at least one of different behavior names, behavior descriptions, and application IDs in the access log, and mark the different behaviors using a behavior identifier.

The behavior classification module 1102 is configured to perform behavior classification according to the behavior identifier and the user ID and the behavior time in the access log to obtain at least one behavior class, so that each behavior class includes the behavior time, the behavior identifier, and the user ID corresponding to each user.

A behavior dividing module 1103, configured to divide the behavior categories according to a difference between behavior times included in the behavior categories to obtain at least one continuous behavior of each user, where the continuous behavior includes at least one behavior category.

Optionally, in this embodiment, the user behavior path analysis device 110 further includes:

the hierarchical division module 1104 is configured to divide behavior categories included in at least one continuous behavior into different hierarchies according to a sequence of behavior time, and identify the different hierarchies by using hierarchy identifiers, where each hierarchy includes a behavior category.

The user behavior path analysis apparatus 110 provided in the embodiment of the present application may be specific hardware on the electronic device 100, or software or firmware installed on the electronic device 100, or the like. The device provided by the embodiment of the present application has the same implementation principle and technical effect as the foregoing method embodiments, and for the sake of brief description, reference may be made to the corresponding contents in the foregoing method embodiments where no part of the device embodiments is mentioned. It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the foregoing systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

The embodiment of the present application further provides an electronic device 100, which includes a processor 130 and a nonvolatile memory 120 storing computer instructions, where when the computer instructions are executed by the processor 130, the electronic device 100 executes the method described in the foregoing method embodiment, and specific implementation may refer to the method embodiment, and is not described herein again.

The embodiment of the present application further provides a storage medium, where a computer program is stored in the storage medium, and when the computer program is executed, the user behavior path analysis method in the foregoing method embodiment is implemented.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in a figure, it need not be further defined or explained in subsequent figures, and moreover, the terms "first", "second", etc. are used merely to distinguish one description from another, and are not to be construed as indicating or implying relative importance.

Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the present disclosure, which should be construed in light of the above teachings. Are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A user behavior path analysis method is applied to electronic equipment, and comprises the following steps:

2. The method of claim 1, wherein dividing the behavior categories according to differences between behavior times included in the behavior categories to obtain at least one continuous behavior for each user comprises:

3. The method of claim 2, wherein the classifying the behavior classes according to their labels to obtain at least one continuous behavior for each user comprises:

4. The method according to claim 1, wherein after the behavior categories are divided according to the difference between the behavior times included in the behavior categories to obtain at least one continuous behavior for each user, the method further comprises:

5. The method according to claim 4, wherein after dividing the behavior categories included in at least one of the continuous behaviors into different hierarchies according to the chronological order of the behaviors and identifying the different hierarchies using hierarchy identifiers, the method further comprises:

6. The method of claim 1, before defining the user behavior of each user according to the obtained access log, the method further comprising:

7. A user behavior path analysis device is applied to electronic equipment and comprises:

8. The apparatus of claim 7, further comprising:

9. An electronic device comprising a processor and a non-volatile memory storing computer instructions that, when executed by the processor, perform the user behavior path analysis method of any one of claims 1-6.

10. A storage medium having stored therein a computer program that, when executed, implements the user behavior path analysis method of any one of claims 1 to 6.