Collaborative filtering by mining association rules from user access sequences

Mei-Ling Shyu, Choochart Haruechaiyasak, Shu Ching Chen, Na Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

28 Citations (Scopus)

Abstract

Recent research in mining user access patterns for predicting Web page requests focuses only on consecutive sequential Web page accesses, i.e., pages which are accessed by following the hyperlinks. In this paper, we propose a new method for mining user access patterns that allows the prediction of multiple non-consecutive Web pages, i.e., any pages within the Web site. Our approach consists of two major steps. First, the shortest path algorithm in graph theory is applied to find the distances between Web pages. In order to capture user access behavior on the Web, the distances are derived from user access sequences, as opposed to static structural hyperlinks. We refer to these distances as Minimum Reaching Distance (MRD) information. The association rule mining (ARM) technique is then applied to form a set of predictive rules which are further refined and pruned by using the MRD information. The proposed approach is applied as a collaborative filtering technique to recommend Web pages within a Web site. Experimental results demonstrate that our approach improves performance over the existing Markov model approach in terms of precision and recall, and also has a better potential of reducing the user access time on the Web.

Original languageEnglish
Title of host publicationProceedings - International Workshop on Challenges in Web Information Retrieval and Integration, WIRI'05
Pages128-133
Number of pages6
Volume2005
DOIs
StatePublished - Dec 1 2005
EventInternational Workshop on Challenges in Web Information Retrieval and Integration, WIRI'05 - Tokyo, Japan
Duration: Apr 8 2005Apr 9 2005

Other

OtherInternational Workshop on Challenges in Web Information Retrieval and Integration, WIRI'05
CountryJapan
CityTokyo
Period4/8/054/9/05

Fingerprint

Collaborative filtering
Association rules
Websites
Graph theory

Keywords

  • Association rule mining
  • Collaborative filtering
  • Web data extraction
  • Web log/navigation path analysis

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Shyu, M-L., Haruechaiyasak, C., Chen, S. C., & Zhao, N. (2005). Collaborative filtering by mining association rules from user access sequences. In Proceedings - International Workshop on Challenges in Web Information Retrieval and Integration, WIRI'05 (Vol. 2005, pp. 128-133). [1553005] https://doi.org/10.1109/WIRI.2005.14

Collaborative filtering by mining association rules from user access sequences. / Shyu, Mei-Ling; Haruechaiyasak, Choochart; Chen, Shu Ching; Zhao, Na.

Proceedings - International Workshop on Challenges in Web Information Retrieval and Integration, WIRI'05. Vol. 2005 2005. p. 128-133 1553005.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shyu, M-L, Haruechaiyasak, C, Chen, SC & Zhao, N 2005, Collaborative filtering by mining association rules from user access sequences. in Proceedings - International Workshop on Challenges in Web Information Retrieval and Integration, WIRI'05. vol. 2005, 1553005, pp. 128-133, International Workshop on Challenges in Web Information Retrieval and Integration, WIRI'05, Tokyo, Japan, 4/8/05. https://doi.org/10.1109/WIRI.2005.14
Shyu M-L, Haruechaiyasak C, Chen SC, Zhao N. Collaborative filtering by mining association rules from user access sequences. In Proceedings - International Workshop on Challenges in Web Information Retrieval and Integration, WIRI'05. Vol. 2005. 2005. p. 128-133. 1553005 https://doi.org/10.1109/WIRI.2005.14
Shyu, Mei-Ling ; Haruechaiyasak, Choochart ; Chen, Shu Ching ; Zhao, Na. / Collaborative filtering by mining association rules from user access sequences. Proceedings - International Workshop on Challenges in Web Information Retrieval and Integration, WIRI'05. Vol. 2005 2005. pp. 128-133
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