Mining and prediction of temporal navigation patterns for personalized services in E-commerce

S. Tseng*, Jeng Chuan Chang, Kawuu W. Lin

*Corresponding author for this work

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

3 Scopus citations

Abstract

With the rapid development of E-commerce, the topic of mining and predicting users' navigation patterns has attracted significant attention due to the wide applications like personalized services in E-commerce. Although a number of studies have been done on this topic, few of them take into account the temporal property for web user's navigation patterns. In this paper, we propose a novel method named Temporal N-Gram (TN-Gram) for constructing prediction models of Web user navigation by considering the temporality property in Web usage evolution. Moreover, three kinds of new measures are proposed for evaluating the temporal evolution of navigation patterns under different time periods. Through experimental evaluation on both of real-life and simulated datasets, the proposed TN-Gram model is shown to outperform other approaches like N-gram modeling in terms of the prediction precision, in particular when the web user's navigating behavior changes with temporal evolution.

Original languageEnglish
Title of host publicationApplied Computing 2006 - The 21st Annual ACM Symposium on Applied Computing - Proceedings of the 2006 ACM Symposium on Applied Computing
Pages867-871
Number of pages5
DOIs
StatePublished - 21 Nov 2006
Event2006 ACM Symposium on Applied Computing - Dijon, France
Duration: 23 Apr 200627 Apr 2006

Publication series

NameProceedings of the ACM Symposium on Applied Computing
Volume1

Conference

Conference2006 ACM Symposium on Applied Computing
CountryFrance
CityDijon
Period23/04/0627/04/06

Keywords

  • Data mining
  • Navigation patterns
  • Personalized services
  • Temporal patterns

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    Tseng, S., Chang, J. C., & Lin, K. W. (2006). Mining and prediction of temporal navigation patterns for personalized services in E-commerce. In Applied Computing 2006 - The 21st Annual ACM Symposium on Applied Computing - Proceedings of the 2006 ACM Symposium on Applied Computing (pp. 867-871). (Proceedings of the ACM Symposium on Applied Computing; Vol. 1). https://doi.org/10.1145/1141277.1141478