On the temporal analysis for improved hybrid recommendations

T. Y. Tang, P. Winoto, Chun Chung Chan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

13 Citations (Scopus)


Recommender systems address the issue of information overload by providing personalized recommendations towards a target user based upon a history of his/her likes and dislikes. Collaborative filtering and content-based methods are two most commonly used approaches in most recommender systems. Although each of them has both advantages and disadvantages in providing high quality recommendations, a hybrid recommendation mechanism incorporating components from both of the methods would yield satisfactory results in many situations. Unfortunately, most hybrid approaches have focused on the contents of items but the temporal feature of them, which is the theme of our study here. In particular, we argue, here in the context of movie recommendation, that movie's production year, which reflects the situational environment where the movies were filmed, might affect the values of the movies being recommended, and in turn significantly affect target user's future preferences. We called it the temporal effects of the items on the performance of the recommender systems. We perform some experiments on the famous MovieLens data sets, and significant results were obtained from our experiments. We believe that the temporal features of items can be exploited to not only scale down the huge amount of data set, especially for Web-based recommender system, but also allow us to quickly select high quality candidate sets to make more accurate recommendations.
Original languageEnglish
Title of host publicationProceedings - IEEE/WIC International Conference on Web Intelligence, WI 2003
Number of pages7
ISBN (Electronic)0769519326, 9780769519326
Publication statusPublished - 1 Jan 2003
EventIEEE/WIC International Conference on Web Intelligence, WI 2003 - Halifax, Canada
Duration: 13 Oct 200317 Oct 2003


ConferenceIEEE/WIC International Conference on Web Intelligence, WI 2003


  • Collaboration
  • Filtering
  • History
  • Motion pictures
  • Production
  • Recommender systems

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Information Systems and Management


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