A NGD Based Document Filtering System for Limited User Feedback
| Autor: | Hao-ping Lee, 李浩平 |
|---|---|
| Rok vydání: | 2011 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 99 Due to the development of the Internet, people can access mass information easily from a variety of search engines and portal; however, in the meantime, people also have to face the problem of “information overload”. Therefore, how to extract useful information for the users from the mass information has become a vital issue in the information explosion era, and the research of information filtering has been caused. Nevertheless, different from the traditional classification which focused on the classification of static information, information filtering system has to face the situation that the interests of users would change dynamically. The phenomenon that the distribution of data changes over time is called “Concept drift”. When concept drift happens to the interests of users, the information filtering system has to have sufficient ability to detect the happening of concept drift; furthermore, it has to adjust and update the interest models of users in time. Traditionally, the information filtering system has to collect a lot of feedback information to reflect the interest change of user, so that the filer could be stable and effective. In order to improve the inefficiency of information filtering system when concept drift happens, this research applied the characteristic of NGD, which could recognize the relationships between the meanings of different terms, to propose a dynamic information filtering system which could establish the interest models of users by limited training documents. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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