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http://dx.doi.org/10.3745/KIPSTD.2009.16-D.3.423

Development and Application of An Adaptive Web Site Construction Algorithm  

Choi, Yun-Hee (서울오류남초등학교)
Jun, Woo-Chun (서울교육대학교 컴퓨터교육과)
Publication Information
The KIPS Transactions:PartD / v.16D, no.3, 2009 , pp. 423-432 More about this Journal
Abstract
Advances in information and communication technologies are changing our society greatly. In knowledge-based society, information can be obtained easily via communication tools such as web and e-mail. However, obtaining right and up-to-date information is difficult in spite of overflowing information. The concept of adaptive web site has been initiated recently. The purpose of the site is to provide information only users want out of tons of data gathered. In this paper, an algorithm is developed for adaptive web site construction. The proposed algorithm is based on association rules that are major principle in adaptive web site construction. The algorithm is constructed by analysing log data in web server and extracting meaning documents through finding behavior patterns of users. The proposed algorithm has the following characteristics. First, it is superior to existing algorithms using association rules in time complexity. Its superiority is proved theoretically. Second, the proposed algorithm is effective in space complexity. This is due to that it does not need any intermediate products except a linked list that is essential for finding frequent item sets.
Keywords
Association Rules; Adaptive Web Site;
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1 주종성, 다중항목지지도를 고려한 수정된 H-마이닝 빈발 패턴탐색, 석사학위논문, 한양대학교, 2005
2 박종수, 웹 로그 파일에서 빈발항목 집합 탐사, 성신여자대학교 기초과학연구지 Vol.17 pp.1-16, 1999
3 Dai, Y. M., A data mining system for mining library borrowing history records, A Master's Thesis, National Chiao-Tung University, 2001
4 Goebel, M., Gruenwald, L., A survey of data mining software tools, ACM SIGKDD Exploration Vol.1 Issue1, pp.20-33, 1999   DOI
5 Gopalan, R. P., Sucahyo, Y. G., Fast frequent itemset mining using compressed data representation, Applied Informatics 2003. pp.1203-1208, 2003
6 Mehmed Kantardzic, Data Mining : Concepts, Models, Methods and Algorithms, Wiley-IEEE Press, 2002
7 Pei, J., Han, H., Lu, H., Nishio, S., Tang, S., Yang, D., H-mine: hyper-struct mining of frequent patterns in large databases, In Proceedings of the 2001 IEEE International Conference on Data Mining (ICDM'01), pp.441-448, 2001
8 Prasetyo, B., Pramudiono, I., Kitsuregawa, M., Hmine- rev: toward H-mine parellelization on mining frequent patterns in large databases, 情報處理學會技術硏究報告 2005-DBS-137(44), No.68, pp.329-336, 2005
9 고경자, 웹 마이닝을 이용한 적응형 웹 사이트 구축에 관한 연구, 석사학위논문, 경기대학교, 2001
10 김영태, 웹 로그와 구매 DB를 이용한 개인화 시스템에 관한 연구, 석사학위논문, 조선대학교, 2004
11 박종배, 클릭스트림 분석을 이용한 사용자별 메뉴 생성 시스템의 설계 및 구현, 석사학위논문, 순천대학교, 2005
12 indeutation 오근정, 쇼핑몰의 상품간 연관규칙 탐색을 위한 빈발항목 발견에 관한 연구 : Matrix 접근법, 석사학위논문, 대전대학교, 2004
13 Agrawl, R., Srikant, R., Fast algorithm for mining association rules, In Proc. 1994 Int. Conf. Very Large Data Bases (VLDB'94), pp.487-499, 1994
14 Borgelt, C., Keeping things simple : Finding frequent item sets by recursive elimination, Workshop Open Source Data Mining Software (OSDM'05, Chicago, IL), pp.66-70, 2005   DOI
15 박인창, L2-tree 기반의 빈발항목집합 탐사 기법, 석사학위논문, 연세대학교, 2003
16 이정민, 연관규칙을 이용한 적응형 학교 웹사이트 구축 알고리즘, 석사학위논문, 서울교육대학교, 2005
17 Pei, J., Pattern growth methods for frequent pattern mining, the degree of doctor of philosophy, Simon Fraser university, 2002