A clickstream-based collaborative filtering recommendation model for e-commerce

Dong Ho Kim, Il Im, Vijayalakshmi Atluri

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

4 Citations (Scopus)

Abstract

In recent years, clickstream-based collaborative filtering (CCF) recommendation models have received much attention mainly due to their scalability. The common CCF recommendation models are Markov modesl, sequential association rules, association rules, and clustering. The models have shown the trade-off relationship between precision and recall in performance. To address the trade-off relationship, some study has combined two or more different models or applied multi-order models. The increase of recommendation effectiveness by these models is also at best marginal. To increase recall while minimizing the loss of precision and therefore to increase overall performance measured by the F value, we build a sequentially applied model (SAM) by applying the individual models in tandem in an order determined through a learning process. We evaluated SAM over the individual models with Web usage data, and the result is promising.

Original languageEnglish
Title of host publicationProceedings - Seventh IEEE International Conference on E-Commerce Technology, CEC 2005
Pages84-91
Number of pages8
DOIs
Publication statusPublished - 2005
Event7th IEEE International Conference on E-Commerce Technology, CEC 2005 - Munich, Germany
Duration: 2005 Jul 192005 Jul 22

Publication series

NameProceedings - Seventh IEEE International Conference on E-Commerce Technology, CEC 2005
Volume2005

Other

Other7th IEEE International Conference on E-Commerce Technology, CEC 2005
CountryGermany
CityMunich
Period05/7/1905/7/22

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • Cite this

    Kim, D. H., Im, I., & Atluri, V. (2005). A clickstream-based collaborative filtering recommendation model for e-commerce. In Proceedings - Seventh IEEE International Conference on E-Commerce Technology, CEC 2005 (pp. 84-91). [1524032] (Proceedings - Seventh IEEE International Conference on E-Commerce Technology, CEC 2005; Vol. 2005). https://doi.org/10.1109/ICECT.2005.1