The Research On Measurement Of Interest Based On Behavior

The Personalization is very hot and active field in the science research and business application, today. However, most of these systems have some drawbacks after analyzing them, such as, the shortcoming of embodiment of personalization; the heavy burden of the system; the ineffective difference between the current interest and the Permanent interest; the bad efficiency of study; and so on. Furthermore, most of the system concentrate on the web mining of web log, but that web log is not integrity, and not well and truly, so that it will lost many useful information of client if the research is applied by methods of web mining of web log only.In this thesis, we bring forward an fuzzy-based approach, by analyzing behavior, to measure the interest degree of user to single web page, which can enhance the current user interest model limited to the content. In the introduction, the actuality and deficiency are presented, then advanced to the forward; In the second chapter, we described the acknowledge which was used for analyzing the user behavior from the viewpoint of personalization system's constructure, and present a design which was composed with content analyzing and behavior analyzing; According to fuzzy theory capability of the function to return a not sure result is what differentiates fuzzy set theory from the other methods and, to our method , is what gives it its strength. Chapter 3 provide some basic theory of Fuzzy Mathematics used in the method when analyzing behavior. In the fourth chapter, the method, based on fuzzy mathmatics, was dicussed in detail. Looking for suitable membership function and cluster method is the commited step of this method. An improved User Instrest Model was presented in the fifth chapter. Through the consideration of instrest of each page, this Interest Model become more truly ,and the interest measurement of web page is obtained from the analysis of user browsing behavior. In fact, behavior analysis can't stand alone, it can only make personalization system get better performance with other content-based method.Finally, the author experiment on the method discussed above. According to the experimentation and analyses, prove that the method is reliable, and can be applied in personalization system.