연관규칙과 가중 선호도를 이용한 추천시스템 연구

• 영문명: A Study of Recommendation System Using Association Rule and Weighted Preference
• 발행기관: 한국IT서비스학회
• 저자명: 문송철(Song Chul Moon) 조영성(Young Sung Cho)
• 간행물 정보: 『한국IT서비스학회지』한국IT서비스학회지 제13권 제3호, 309~321쪽, 전체 13쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2014.09.30

영문 초록

Recently, due to the advent of ubiquitous computing and the spread of intelligent portable device such as smart phone, iPad and PDA has been amplified, a variety of services and the amount of information has also increased fastly. It is becoming a part of our common life style that the demands for enjoying the wireless internet are increasing anytime or anyplace without any restriction of time and place. And also, the demands for e-commerce and many different items on e-commerce and interesting of associated items are increasing. Existing collaborative filtering (CF), explicit method, can not only reflect exact attributes of item, but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, using a implicit method without onerous question and answer to the users, not used user's profile for rating to reduce customers' searching effort to find out the items with high purchasability, it is necessary for us to analyse the segmentation of customer and item based on customer data and purchase history data, which is able to reflect the attributes of the item in order to improve the accuracy of recommendation. We propose the method of recommendation system using association rule and weighted preference so as to consider many different items on e-commerce and to refect the profit/weight/importance of attributed of a item. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

목차

Abstract

1. 서론

2. 관련 연구

3. 연관규칙과 가중 선호도를 이용한 추천시스템

4. 실험 및 성능 평가

5. 결론 및 향후 과제

References

키워드

Segmentation Method Asociation Rules Recommender System