|
Title:
|
INFORMATION FILTERING SYSTEM WITH A GROUPING GENETIC ALGORITHM |
|
Author(s):
|
Hidekazu Yanagimoto , Michifumi Yoshioka , Toru Fujinaka , Sigeru Omatu |
|
ISBN:
|
972-9027-53-6 |
|
Editors:
|
Pedro Isaías |
|
Year:
|
2002 |
|
Edition:
|
Single |
|
Keywords:
|
Information Retrieval, Information Filtering, Genetic Algorithm, User Modeling . |
|
Type:
|
Short Paper |
|
First Page:
|
716 |
|
Last Page:
|
721 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper Abstract:
|
There are a lot of digital documents since computers and the Internet become spreadwide. In this situation, it is difficult for many users to find out their desirable information. For example, when a user uses search engines to look for the information, he/she gets a lot of results from them. Much attention is recently paid for research on information filtering systems and recommendation systems. We propose the information filtering system with a grouping genetic algorithm. In particular, we deal with users interests that the user has been keeping up with for a long time.
In the proposed method genes are grouped on the basis of their fitness values. Hence, documents are self-organized according to their features. In this paper, we describe the proposed method, and evaluate it by a computer simulation. We compare the method with the relevance feedback. |
|
|
|
|
|
|
