User Preference Mining through Hybrid Collaborative Filtering and Content-Based Filtering in Recommendation System
Summary :
The growth of the Internet has resulted in an increasing need for personalized information systems. The paper describes an autonomous agent, the Web Robot Agent or WebBot, which integrates with the web and acts as a personal recommendation system that cooperates with the user in order to identify interesting pages. The Apriori algorithm extracts the characteristics of the web pages in the form of association words that are semantically related and mines a bag of association words. Using hybrid components from collaborative filtering and content-based filtering, this hybrid recommendation system can overcome the shortcomings associated with traditional recommendation systems. In this paper, we present an improved recommendation system, which uses the user preference mining through hybrid 2-way filtering. The proposed method was tested on a database, and its effectiveness compared with existent methods was proven in on-line experiments.
- Publication
- IEICE TRANSACTIONS on Information Vol.E87-D No.12 pp.2781-2790
- Publication Date
- 2004/12/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Artificial Intelligence and Cognitive Science
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Kyung-Yong JUNG, Jung-Hyun LEE, "User Preference Mining through Hybrid Collaborative Filtering and Content-Based Filtering in Recommendation System" in IEICE TRANSACTIONS on Information,
vol. E87-D, no. 12, pp. 2781-2790, December 2004, doi: .
Abstract: The growth of the Internet has resulted in an increasing need for personalized information systems. The paper describes an autonomous agent, the Web Robot Agent or WebBot, which integrates with the web and acts as a personal recommendation system that cooperates with the user in order to identify interesting pages. The Apriori algorithm extracts the characteristics of the web pages in the form of association words that are semantically related and mines a bag of association words. Using hybrid components from collaborative filtering and content-based filtering, this hybrid recommendation system can overcome the shortcomings associated with traditional recommendation systems. In this paper, we present an improved recommendation system, which uses the user preference mining through hybrid 2-way filtering. The proposed method was tested on a database, and its effectiveness compared with existent methods was proven in on-line experiments.
URL: https://global.ieice.org/en_transactions/information/10.1587/e87-d_12_2781/_p
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@ARTICLE{e87-d_12_2781,
author={Kyung-Yong JUNG, Jung-Hyun LEE, },
journal={IEICE TRANSACTIONS on Information},
title={User Preference Mining through Hybrid Collaborative Filtering and Content-Based Filtering in Recommendation System},
year={2004},
volume={E87-D},
number={12},
pages={2781-2790},
abstract={The growth of the Internet has resulted in an increasing need for personalized information systems. The paper describes an autonomous agent, the Web Robot Agent or WebBot, which integrates with the web and acts as a personal recommendation system that cooperates with the user in order to identify interesting pages. The Apriori algorithm extracts the characteristics of the web pages in the form of association words that are semantically related and mines a bag of association words. Using hybrid components from collaborative filtering and content-based filtering, this hybrid recommendation system can overcome the shortcomings associated with traditional recommendation systems. In this paper, we present an improved recommendation system, which uses the user preference mining through hybrid 2-way filtering. The proposed method was tested on a database, and its effectiveness compared with existent methods was proven in on-line experiments.},
keywords={},
doi={},
ISSN={},
month={December},}
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TY - JOUR
TI - User Preference Mining through Hybrid Collaborative Filtering and Content-Based Filtering in Recommendation System
T2 - IEICE TRANSACTIONS on Information
SP - 2781
EP - 2790
AU - Kyung-Yong JUNG
AU - Jung-Hyun LEE
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E87-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2004
AB - The growth of the Internet has resulted in an increasing need for personalized information systems. The paper describes an autonomous agent, the Web Robot Agent or WebBot, which integrates with the web and acts as a personal recommendation system that cooperates with the user in order to identify interesting pages. The Apriori algorithm extracts the characteristics of the web pages in the form of association words that are semantically related and mines a bag of association words. Using hybrid components from collaborative filtering and content-based filtering, this hybrid recommendation system can overcome the shortcomings associated with traditional recommendation systems. In this paper, we present an improved recommendation system, which uses the user preference mining through hybrid 2-way filtering. The proposed method was tested on a database, and its effectiveness compared with existent methods was proven in on-line experiments.
ER -
English
