TWI443524B - Method and apparatus for tracking and recording user's actions when operating an electronic equipment - Google Patents

Description

User behavior tracking and recording system and method

The invention relates to a data tracking and recording technology, in particular to a tracking and recording system and method for mobile phone user behavior.

At present, the use of smart phones has become more and more extensive. Smart phones have more data processing capabilities, larger memory capacity and multiple functions than traditional feature phones. Through the hardware upgrade, users can expand the software in the smart phone by themselves. Thus, if the entire mobile phone system is represented by a tree structure in which each directory or each application is regarded as a node, the depth and breadth of the tree will be expanded. Referring to Figure 1, a tree structure diagram of a simple mobile phone system is shown. The breadth and depth of the tree structure are both 5.

Based on the tree structure of FIG. 1, if the user needs to execute an application, such as the application 11, the user needs to scroll down 3 layers from the root directory to reach the application 11, which brings great inconvenience to the user. .

In the past, the main ways to solve the above problems are: 1) using the keys of the mobile phone keyboard to create shortcut keys for each application; 2) establishing a quick icon on the main interface of the mobile phone screen. However, for the first method, it is difficult for the user to remember the shortcut keys of each application. The second method also has the following problems: 1) Because the shortcut icon is usually built on the main interface of the screen, and the screen of the mobile phone is limited, the number of shortcut icons is also limited; 2) when the user is not currently browsing the main interface Even if the main interface has a quick icon, it will also cause inconvenience to the user. Taking FIG. 1 as an example, after the user executes the application 11 at the depth 4 and wants to execute the application 8 at the depth 3, the user needs to return to the main interface to check whether there is a shortcut icon of the application 8.

Often, users may only create shortcuts or shortcut icons for frequently used applications or directories. However, as time changes or changes in interests, the applications or directories that users often use may change. For convenience, the user must manually create a shortcut or shortcut icon for the application.

In addition, the above method of establishing shortcut keys or shortcut icons has the following defects: 1) setting shortcut keys or shortcut icons cannot achieve ranking of the importance of the application in the mobile phone to the user; 2) constantly in the smart phone In the case of an upgrade, the number of applications will also increase. Traditional shortcuts or shortcut icons provide a quick link to the application, and cannot analyze the association between applications, or directories and applications. The dependencies between programs. For example, referring to FIG. 1, if the user frequently executes the application 4 and then executes the application 6, the application is dependent on the user.

In view of the above, it is necessary to propose a user behavior tracking and recording system and method, which ranks the importance of an application or a directory according to the behavior of the user, thereby establishing a smart shortcut.

A user behavior tracking and recording system installed in an electronic device. The electronic device includes a plurality of applications and directories. The system includes: a parameter receiving module, configured to receive a user-set frequency standard and a legal rule, wherein the use frequency standard is a value of a number of times of executing an application or a directory, and the phase is Refers to the value of the number of paths used to execute an application or directory; the detection module is used to detect the application or directory currently being executed by the user and to detect the path taken to execute the current application or directory. And storing the path in the storage unit of the electronic device; the frequency calculation module is configured to obtain, from the storage unit, the number of times the current application or the directory has been executed, and add 1 to the number of times, and The modified number is stored in the storage unit; the storage module is configured to store the ID of the current application or directory into a queue of the storage unit when the modified number reaches the set usage frequency standard; Dependency graph creation module for storing the ID and storage unit of the application or directory in the above queue The path establishes a dependency graph; the weight calculation module is configured to calculate the weight of each node in the dependency graph; and the sorting module is configured to use the weight of each node in the dependency graph to depend on the relationship The application or directory in the graphic is sorted; and the display module is configured to display the sorting on the main screen of the electronic device or display a shortcut icon of the application/directory in the sorting.

A user behavior tracking and recording method applied to an electronic device. The method includes: receiving a usage frequency standard set by a user and a legal rule, wherein the usage frequency standard is a value of a number of times of executing an application or a directory, and the phase is said to execute an application or The value of the path used by the directory; detecting the application or directory currently being executed by the user, detecting the path taken by the current application or directory, and storing the path in the storage unit of the electronic device; Obtaining the number of times the current application or directory has been executed from the storage unit, adding 1 to the number of times, and storing the modified number in the storage unit; when the modified number reaches the set frequency of use When the standard is used, the ID of the application or the directory is stored in a queue of the storage unit; when it is determined according to the path stored in the storage unit that there is an application or a directory that satisfies the law in the queue, a first a dependency graph; calculating the weight of each node in the dependency graph; According to the above-described pattern dependencies weights the dependencies graphics application or directory sorting; and displayed on the screen of the main interface of the electronic device or quick sort illustrated ordering the app / directory display.

Compared with the prior art, the user behavior tracking and recording system and method provided by the present invention analyzes the user's preferences by tracking and recording the behavior of the mobile phone user executing the application software or the directory, and is an application in the mobile phone system or The catalog is ranked so that personalized shortcuts can be created for the user.

Referring to Figure 2, there is shown a block diagram of a preferred embodiment of the user behavior tracking and recording system 1 of the present invention. The system 1 can be installed in an electronic device such as a mobile phone, a computer, or the like. The system 1 includes a parameter receiving module 10, a detecting module 11, a frequency calculating module 12, a determining module 13, a storage module 14, a dependency graph building module 15, a weight calculating module 16, and a sorting module. 17 and display module 18. Further, the system 1 further includes a storage unit 19.

The above modules are various programs for performing specific functions, and are more suitable for describing the execution process of the software in the computer than the software program itself. Therefore, the description of the software program in the present invention is described by a module.

The parameter receiving module 10 is configured to receive a frequency of use frequency set by a user and a legal rule. The usage frequency standard is a value of the number of times an application or directory is executed. The value of the number represents the usage habit of the user, that is, when the number of times the user executes an application or a directory reaches the value, the application or directory is used by the user. The phase refers to the value of the number of times the path taken by an application or a directory is executed. For example, after the user executes the application A and directly executes the application B, the application A to the application B is the path for executing the application B. The value of the path also represents the usage habit of the user, that is, when the user uses the path from the application A to the application B to execute the application B for a set number of times, the application A and the application B are described. For the user to have a dependent relationship, in accordance with the law. Further, referring to FIG. 1, if the user frequently executes the application 4 and then executes the application 6, when the number of times of adopting the path exceeds the set phase, the application 4 and the application 6 indicate the use. They have a dependency relationship.

The detecting module 11 is configured to detect a user's behavior, that is, detecting an application or a directory that the user is currently executing, and detecting a path taken to execute the currently executing application or directory, and This path is stored in the storage unit 19.

The frequency calculation module 12 is configured to obtain, from the storage unit 19, the number of times that the currently executing application or directory has been executed, add 1 to the number of times, and store the modified number in the storage unit. 19 in.

The determining module 13 is configured to determine whether the modified number of times reaches the set frequency of use standard.

The storage module 14 is configured to store the ID of the currently executing application or directory into a queue of the storage unit 19 when the modified number reaches the set usage frequency standard.

The determining module 13 is further configured to determine, according to the path stored in the storage unit 19, whether there is an application or a directory that satisfies the legal rule in the queue, that is, after determining to execute an application or a directory in the queue, Whether the number of times the other application or directory in the queue is directly executed satisfies the above-mentioned rules. As shown in FIG. 3A, it is assumed that the user executes the application 2 path usually after the root directory is viewed, and the number of times the path is used satisfies the above-mentioned setting, indicating that the root directory and the application 2 are The user has a dependency relationship. In addition, in FIG. 3A, the application program 2, the application program 4, the application program 4, and the application program 1 also satisfy the above-mentioned legal rules and have a dependency relationship. If the storage unit 19 stores a path, such as the path from the root directory in FIG. 3A to the application 3, but the number of times the path is used has not been met, the root directory and the application 3 are only in the candidate state and have not yet Have a dependency relationship.

The dependency relationship graph creation module 15 is configured to establish an dependency relationship graph when there is an application or a directory in the queue that satisfies the law. Referring to FIG. 3B, a dependency graph is established based on the dependencies between the applications or directories in FIG. 3A. Among them, because application 3 has not yet established a dependency relationship with any application or directory, it is in a candidate state.

The weight calculation module 16 is configured to calculate the weight of each node in the dependency graph. Referring to FIG. 4A, each node in the dependency graph is not subjected to the initial weight map calculated by the weight calculation module 16. There are 5 nodes in the dependency graph, so the initial weight of each node is 0.2. The weight calculation module 16 calculates the weight PR(P _i ) of each node in the dependent relationship graph by using the Pagerank method, and the formula is:

Where Equation 2 is the expansion of Equation 1. In the above formula, P ₁ to P _j are _j nodes connected to the node P _i . In FIG. 3B , the application 1, the application 4 and the application 2 are nodes connected to the root directory; the PR (P _j ) is a node. The weight of P _j , such as PR (P ₁ ) is the weight of the P ₁ node, and so on; Outdegree (P _j ) is the number of external connections of the node P _j , as shown in application 4 in Figure 3B, The number of nodes is 2, which is application 1 and root directory respectively; d represents a probability value, indicating the probability that the user randomly selects a node, usually 0.15; and (1-d) indicates that the user follows the link relationship. The probability of selecting the node, such as 1-0.15=0.85; n represents the number of all nodes included in the entire dependency graph, as shown in Figure 3B, n=5.

The sorting module 17 is configured to sort the applications or directories in the dependency graph according to the weights in the dependency graph. Usually, the sorting method is a power-down arrangement.

The display module 18 is configured to display the sorting or display a shortcut icon of the application or directory in the sorting on the main screen of the electronic device.

Referring to FIG. 5, it is a flowchart of an implementation of a preferred embodiment of the user behavior tracking and recording method of the present invention.

In step S10, the parameter receiving module 10 receives the usage frequency standard set by the user and the legal rule.

In step S11, the detecting module 11 detects an application or a directory currently being executed by the user, and detects a path taken by the currently executing application or directory, and stores the path in the storage unit 19.

In step S12, the frequency calculation module 12 acquires from the storage unit 19 the number of times that the currently executing application or directory has been executed.

In step S13, the frequency calculation module 12 adds 1 to the number of times and stores the modified number in the storage unit 19.

In step S14, the determining module 13 determines whether the modified number of times has reached the set usage frequency standard. If the set frequency standard is not reached, the process ends.

If the set frequency standard is reached, the storage module 14 stores the ID of the application or directory in a queue of the storage unit 19 in step S15.

In step S16, the judging module 13 further determines, according to the path stored in the storage unit 19, whether there is an application or a directory that satisfies the above-mentioned law in the queue. If there is no application or directory that meets the legal requirements, the process ends. Otherwise, if such an application or directory exists, the process proceeds to step S17.

In step S17, the dependency graph creating module 15 creates a first dependency graph according to the ID and path of the application or directory stored in the storage unit 19.

In step S18, the weight calculation module 16 calculates the weight of each node in the dependency graph. The weight calculation module 16 calculates the weight PR(P _i) of each node in the dependent relationship graph by using the Pagerank method, and the formula is:

Where Equation 2 is the expansion of Equation 1. In the above formula, P ₁ to P _j are _j nodes connected to the node P _i . In FIG. 3B , the application 1, the application 4 and the application 2 are nodes connected to the root directory; the PR (P _j ) is a node. The weight of P _j , such as PR (P ₁ ) is the weight of the P ₁ node, and so on; Outdegree (P _j ) is the number of external connections of the node P _j , as shown in application 4 in Figure 3B, The number of nodes is 2, which is application 1 and root directory respectively; d represents a probability value, indicating the probability that the user randomly selects a node, usually 0.15; and (1-d) indicates that the user follows the link relationship. The probability of selecting the node, such as 1-0.15=0.85; n represents the number of all nodes included in the entire dependency graph, as shown in Figure 3B, n=5.

In step S19, the detecting module 11 detects whether the user needs to establish a second dependency graph based on the currently executing application or directory. The first dependency graph above represents the dependencies between all applications or directories that meet the set frequency of use criteria. If the user is currently executing an application or a directory, the user may only care about the application or directory associated with the currently executing application or directory, ie after executing the currently executing application or directory. The user usually cares about the application or directory that is executed immediately. Therefore, the user needs to create a second dependency graph based on the current application or directory. In this embodiment, a hot key may be set on an electronic device, such as a keyboard or other device of the mobile phone, such as a combination of a "*" sign and a "#" sign, when the detecting module 11 detects that the hot key is pressed. When it is down, it is determined that the user needs to establish a second dependency graph based on the currently executing application or directory.

In step S20, the dependency graph creation module 15 creates a second dependency graph based on the current application or directory reference, and the weight calculation module 16 calculates the weight of each node in the second dependency graph. The second dependency relationship graph can be seen in FIG. 6.

In step S21, the sorting module 17 sorts the applications or directories in the dependency graph according to the weights in the first or second dependency graph. Usually, the sorting method is a power-down arrangement.

In step S22, the display module 18 displays the sorting or displaying a shortcut icon of the application/directory in the sorting on the main screen of the electronic device.

The above is only the preferred embodiment of the present invention, and has been used in a wide range of ways. Any other equivalent changes or modifications which are not departing from the spirit of the present invention should be included in the following claims. Inside.

1. . . User behavior tracking and recording system

10. . . Parameter receiving module

11. . . Detection module

12. . . Frequency calculation module

13. . . Judging module

14. . . Storage module

15. . . Dependent relationship graph creation module

16. . . Weight calculation module

17. . . Sorting module

18. . . Display module

19. . . Storage unit

Figure 1 is a tree structure diagram of a mobile phone system.

2 is a block diagram of a preferred embodiment of the user behavior tracking and recording system of the present invention.

3 is a graph of the dependency relationship of a preferred embodiment of the user behavior tracking and recording system of the present invention.

Figure 4 is a graph of the dependency relationship after calculating the weight.

FIG. 5 is a flow chart showing an implementation of a preferred embodiment of the user behavior tracking and recording method of the present invention.

6 is a diagram of a dependency relationship established by a preferred embodiment of the user behavior tracking and recording system of the present invention based on a currently executing application or directory.

1. . . User behavior tracking and recording system

10. . . Parameter receiving module

11. . . Detection module

12. . . Frequency calculation module

13. . . Judging module

14. . . Storage module

15. . . Dependent relationship graph creation module

16. . . Weight calculation module

17. . . Sorting module

18. . . Display module

19. . . Storage unit

Claims (8)

A user behavior tracking and recording system, the system is installed in an electronic device, the electronic device includes a plurality of applications and directories, wherein the system includes: a parameter receiving module, configured to receive a user-set frequency of use and According to the law, wherein the frequency of use standard is the number of times the execution of an application or directory, and the phase is the number of times the path used to execute an application or directory; the detection module For detecting an application or directory currently being executed by the user, detecting a path used to execute the current application or directory, and storing the path in a storage unit of the electronic device; Obtaining, from the storage unit, the number of times the current application or directory has been executed, adding 1 to the number of times, and storing the modified number in the storage unit; and storing the module for modifying When the number of times reaches the set usage frequency standard, the ID of the current application or directory is stored to the above storage list. a dependency graph creation module for establishing an dependency graph according to an ID of an application or a directory in the queue and a path stored in the storage unit; a weight calculation module for calculating the above The weight of each node in the dependency graph; the sorting module is configured to sort the application or directory in the dependency graph according to the weight of each node in the dependency graph; and the display module is used for The sorting or displaying a quick icon of the application/directory in the sorting is displayed on the main screen of the electronic device. The user behavior tracking and recording system according to claim 1, wherein the weight calculation module calculates the weight of each node in the dependent relationship graph through the Pagerank method. The user behavior tracking and recording system of claim 1, wherein the electronic device is a mobile phone or a computer. The user behavior tracking and recording system of claim 1, wherein the sorting module sorts the applications or directories in the dependency graph by a power-down arrangement method. A user behavior tracking and recording method is applied to an electronic device, the method comprising: receiving a usage frequency standard set by a user and a legal rule, wherein the usage frequency standard is executing an application or a directory. The value of the number of times, and the phase is the number of times the path taken by an application or directory is executed; the application or directory currently being executed by the user is detected, and the current application or directory is detected and executed. The adopted path is stored in the storage unit of the electronic device; the number of times the current application or directory has been executed is obtained from the storage unit, and 1 is added to the number of times, and the modified number is Stored in the storage unit; when the modified number reaches the set frequency of use standard, the ID of the application or directory is stored in a queue of the storage unit; when the path is determined according to the path stored in the storage unit Create a first in the queue when there is an application or directory that satisfies the law Depending on the relationship graph; calculating the weight of each node in the first dependency graph; sorting the application or directory in the first dependency graph according to the weight of each node in the first dependency graph; And displaying the sorting or displaying a quick icon of the application/directory in the sorting on the main screen of the electronic device. The user behavior tracking and recording method according to claim 5, wherein the calculating the weight of each node in the first dependency graph is using the Pagerank method. The method for tracking and recording user behavior as described in claim 5, the method further comprising: detecting whether the user needs to establish a second dependency graph based on the current application or directory; and when needed A second dependency graph is created based on the current application or directory reference, and the weight of each node in the second dependent graph is calculated. The user behavior tracking and recording method according to claim 5, wherein the sorting of the application or the directory in the first dependency graph adopts a power-down arrangement method.