A Term Categorization Approach to Discovery of Personal Preferences from Web Clients
Date Issued
2006
Date
2006
Author(s)
Stu, Jay
DOI
en-US
Abstract
This thesis is developed for discovering the personal preferences from different data sources that stored in web client side like personal computers. To determine the personal preferences, we first extract key terms from different data sources to be the material of the next step, there are three major data sources：search keywords, browsed pages and e-mails. And then we use term categorization method on the key terms to generate user profiles that contains the distributions of different categories. After the simple method, we do some observations of five users to discuss the appearance of the personal categories.
This method is really simple and has more space to discuss about the transformation between term categories and personal preferences. We hope the simple method can be a potential way to perform personalization applications, like personalized search, personal information filtering or recommendation system.
Subjects
個人化
使用者歸檔化
術語分類
使用者分析
Personalization
User profiling
Term categorization
User analysis
Type
other