Research On Web-Based User Access Information Mining

As a method of knowledge discovery, data mining has been widely used, and was the most active domain of database. Web mining is to use the traditional data mining technologies to extract information and knowledge in the Web environment. The web usage mining is the most wide used method, which is used in the field of e-commerce, internet ads, intelligent recommendation system, internet marketing, and intelligent decision support. A good model of web mining is the key to the success of web usage mining, this dissertation will do some research.The dissertation will improve and implement several methods and arithmetic based on the research of the theory and achievement, which is about web user access information mining. This dissertation will design the database to present corresponding data. Then construct a Web user access information mining system model bade on database, and realize several functional module.Data preprocessing is the preparation of web mining. This dissertation will realize data cleaning in SQLServer2000, and introduce method of data cleaning based on the character matching of the crawler. In the phase of user identifying, method based on Cookie, ip, and agent is used. This dissertation gives the concrete arithmetic of session identification and transaction identification, which uses maximum forward path.Pattern discovery is the key to web mining. This dissertation first constructs data presentation of the user access interesting dimension, uses concept hierarchy to induct the page data, then educes the data set suitable to BP networks, finally uses BP networks to constructs a classifier. Then this dissertation introduces and realizes arithmetic offrequent access path based on association rules and sequential mode. At last, this dissertation creates a Matlab arithmetic, which is extensible and practicable, to calculate the relation matrix and statistic analysis.On the ground of work above, this dissertation presents a Web mining system model bade on database, and describes and analyses every module. This model allows that all the operation be based on database. All pattern discovered should be involved in database so that we can manage and apply pattern discovered easily. This dissertation applies web user access information mining to shanghai agriculture information, and finds several useful patterns. The experience data proves that web user access information mining system is practical and effective.The dissertation uses SQL server 2000 as database system, and uses SQL sentence to implement data preprocess. The dissertation uses C++ and Matlab to develop all the function. Web user access information mining is the widely used web mining technique. It can know the interest of users, improve site structure, provide customized service, better marketing policy, recommend and predict the user's behavior. The model given in this dissertation is applicable. Research of this dissertation has theoretical importance and practical value to web user access information mining.