Deep user behavior Multidimensional in-depth analysis of notes

Source: Internet
Author: User

The intermediary transaction SEO diagnoses Taobao guest stationmaster buys the Cloud host technology Hall

At present, all the analysis of user behavior is the following kinds of modes: User registration information, custom list, operation record, user history track tracking, etc. But these are only the tip of the iceberg in the user behavior analysis, in the actual analysis process, the dimension (www.vdoing.com) carries on the weight ordering of a lot of information, refines the core information to construct a 3 dimensional statistical analysis system.

  

For a new site, the user behavior analysis, the most lack of users in the station's behavior trajectory. Because there is not a certain amount of data, it is difficult to pass the normal analysis, there is no way to cluster analysis, can not establish the characteristics of the group. If a new station wants to be able to do in the user behavior analysis and the excavation has certain function, in uses the general statistics and the analysis situation will be very difficult, may want to trace the user's all tracks, then the unceasing precipitation can gradually realize. So really want to analyze the characteristics of the site users, in the traditional statistical methods, it is difficult to complete in a very short time, based on this situation, resulting in a short period of time to complete the user behavior analysis, if completed, the results are also difficult to accurate.

For a website that already has more than million members, the user behavior Analysis and mining, the first step in the traditional statistical analysis process is to separate users, which is also a very difficult thing. Only after the separation of users can find valuable users, in-depth analysis, the use of traditional methods, the difficulty will be quite large.

For any of the above questions, or for anyone who is active on the Internet, can define the access process of any user, that is, a person, an area, a network environment, a computing environment, a need to find or handle something, and then generate some behavior to access a Web site, The data are refined and analyzed, which solves the depth mining of user access analysis.

The dimensions decompose their behavior into this process:

1. Someone (gender, age, occupation)

2, in a certain area (physical address, such as: Beijing)

3, in a network environment (operators, such as: Beijing Telecom ADSL)

4, the use of a computing environment (operating system, ie, etc.)

5, need to find or deal with something (such as: find information or browse)

6, then generate access to a Web site some behavior (mouse events ...). )

Website traffic statistics System, is one of the most important tools to excavate website user behavior, because the statistic system is the most detailed record of the visitor behavior process, we divide the data mining into 3 stages,

The first phase is: data collection and statistics.

The second stage is to filter and analyze the collected data,

The third stage: that is, the data has been filtered and preliminary analysis of clustering and so on, mining the value points or methods contained therein.

But at present all website traffic statistic system only has done to the first level of the data, namely: the user partial information statistics, even these partial data also did not obtain completely. Therefore, the depth of user analysis of the site is still a very challenging job, for the data analysis field, which difficult, which is far more difficult for people to imagine. Based on the user's behavior process, we can simply classify as follows, and define the user behavior as a system of 3 dimensional integrated information.

1, a user (user gender, age and other core data)

2, in a certain period of time (with the passage of natural time, the normal time of the record)

3, produced a certain behavior (network behavior can be divided into 2 kinds of concrete embodiment, namely: 1, keyboard operation. 2, mouse behavior. For keyboard operation information, basically is completely abandoned, because of the basic principles of user privacy, which belong to the statistical forbidden. For the mouse behavior, only including the user mouse trajectory, mouse click URL event records, technology can be achieved, while not directly related to the user's personal privacy, or relatively few, may bring less harm

  

Based on these process information, we generalize the user access process and refine the core information of the access process.

1, a user, the core information include: User sex, user age, user career

This data can only be a probabilistic data, for the following reasons: In the case of a certain base, statistics of a large number of known sex, the age of the user's mouse trajectory behavior characteristics summed up their behavior characteristics, to find a suitable trajectory algorithm, but the trajectory algorithm is based on the benchmark behavior database probability statistics, So the data can only be expressed in the form of probability in this system.

  

2, the user behavior, the core information includes: Mouse mouse slide track, mouse click Hot Zone, mouse click Time sequence

  

  

3, the content information, the core information includes: the mouse clicks the URL to attach the text content, carries on the word segmentation analysis to the attached text, determines its content category as well as the text characteristic.

  

To be continued, dimension statistics (www.vdoing.com)

Hot Zone Map of a website user

  

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