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A method and device for monitoring effective visits of application programs

An application and access technology, applied in the computer field, can solve the problems of ineffective access, cheating of APP usage, and increased usage.

Active Publication Date: 2011-12-14
BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] The number of visits to an application program (APP) is usually a key criterion for evaluating APPs, sorting APPs, and even allocating resources. Therefore, there may be cheating behaviors aimed at APP usage, and the cheating behaviors may come from the APP developers themselves, such as Repeatedly clicking the link of an APP many times leads to an increase in the usage of the monitored APP, but the user who clicks the link of the APP may not actually use the APP, so the visit to the APP is not a valid visit

Method used

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  • A method and device for monitoring effective visits of application programs
  • A method and device for monitoring effective visits of application programs
  • A method and device for monitoring effective visits of application programs

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0077] figure 1 The flow chart of the method for mining APP effective access behavior patterns provided by Embodiment 1 of the present invention, as shown in figure 1 As shown, the specific mining process may include the following steps:

[0078] Step 101: Obtain user behavior data.

[0079] In this step, user behavior data within a set time range can be obtained from user access logs.

[0080] Step 102: Divide user behavior data into different sessions according to searches.

[0081] A session can include multiple pieces of user behavior data, representing a search and the behavior after the search, such as click and loading behavior. In addition to dividing sessions according to search, user behavior data can also be divided into different sessions according to clicks. At this time, a session represents a click and the behavior after the click. User behavior data can also be divided into different sessions according to loading. At this time, a session represents a loadin...

Embodiment 2

[0091] figure 2 The flow chart of the method for monitoring the effective visits of APP provided by Embodiment 2 of the present invention, such as figure 2 As shown, the method may include the following steps:

[0092] Step 201: Obtain user behavior data.

[0093] Usually, user behavior data is recorded in the user access log. In this step, the user behavior data can be obtained from the user access log.

[0094] Wherein, the user behavior data may include but not limited to: behavior data of searching APP, clicking APP behavior data, loading APP behavior data and dwell time corresponding to various user behaviors.

[0095] Step 202: Verify the validity of the user behavior data, and filter out the user behavior data that fails the verification.

[0096] The aforementioned validity verification includes but is not limited to: cookie verification, key verification or reference (refer) verification.

[0097] Wherein, when performing cookie verification, if the cookie is em...

Embodiment 3

[0122] Figure 4 The structure diagram of the device for mining APP effective access behavior patterns provided by Embodiment 3 of the present invention, as shown in Figure 4 As shown, the apparatus may include: a data acquisition unit 400 , a session segmentation unit 410 , a behavior sorting unit 420 , a session determination unit 430 and a pattern extraction unit 440 .

[0123] The data acquisition unit 400 acquires user behavior data.

[0124] The session segmentation unit 410 divides the user behavior data into sessions according to the preset user behavior, and each session represents the preset user behavior and the behavior after the preset user behavior. Wherein, the preset user behavior may include: a behavior of searching for an APP, a behavior of clicking an APP, or a behavior of loading an APP.

[0125] The behavior sorting unit 420 sorts the user behavior data in each session according to time.

[0126] The session determination unit 430 determines the sessio...

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Abstract

The present invention provides a method and device for monitoring effective visits of an application program (APP), wherein the method includes: acquiring user behavior data; User behavior data of access behavior patterns, the effective access behavior patterns include: loading the APP and staying on the APP running page for a time greater than a preset time threshold; based on user behavior data statistics that conform to the effective access behavior patterns The effective number of visits to the APP. The present invention can accurately identify the valid visits to APPs and count the effective visits of APPs, so as to make it a basis for accurately evaluating APPs, sorting APPs, or allocating resources reasonably.

Description

【Technical field】 [0001] The invention relates to the field of computer technology, in particular to a method and a device for monitoring effective visits of an application program (APP). 【Background technique】 [0002] The number of visits to an application program (APP) is usually a key criterion for evaluating APPs, sorting APPs, and even allocating resources. Therefore, there may be cheating behaviors aimed at APP usage, and the cheating behaviors may come from the APP developers themselves, such as Repeatedly clicking the link of an APP many times leads to an increase in the monitored usage of the APP, but the user who clicks the link of the APP may not actually use the APP, so the visit to the APP is not a valid visit. [0003] Therefore, in order to accurately evaluate APPs, sort APPs, or allocate resources reasonably, how to monitor the effective visits of APPs has become an urgent problem to be solved. 【Content of invention】 [0004] The present invention provide...

Claims

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Application Information

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IPC IPC(8): G06F11/34
Inventor 周俊杨然张天龙朱建庭望金蓉刘建国
Owner BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
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