Using incremental clustering technique in collaborative filtering data update

Xiwei Wang, Jun Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Collaborative filtering (CF) techniques are widely used by online shops in their recommender systems. It is well known that the nonnegative matrix factorization (NMF) based CF algorithms are popular and can provide reasonable product recommendations. However, the dimensions of the factor matrices in NMF need to be predetermined and updated when necessary. Moreover, data arrives in every second so the recommender systems must be capable of updating the fast growing data in a timely manner. In this paper, we propose an approach that incorporates incremental clustering technique into NMF based data update algorithm which can determine the dimensions of the factor matrices and update them automatically. The approach clusters users' and items' auxiliary information and uses them as constraints in NMF for data update. The cluster quantities are used as the dimensions of the factor matrices. With more data coming in, the incremental clustering algorithm determines whether to increase the number of clusters or merge the existing clusters. Experiments on three different datasets (MovieLens, Sushi and LibimSeTi) are conducted to examine the proposed approach. The results show that our approach can update the data quickly and provide encouraging prediction accuracy.

Original languageEnglish
Title of host publicationProceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014
EditorsElisa Bertino, Bhavani Thuraisingham, Ling Liu, James Joshi
Pages420-427
Number of pages8
ISBN (Electronic)9781479958801
DOIs
StatePublished - Feb 27 2014
Event15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014 - San Francisco, United States
Duration: Aug 13 2014Aug 15 2014

Publication series

NameProceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014

Conference

Conference15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014
Country/TerritoryUnited States
CitySan Francisco
Period8/13/148/15/14

ASJC Scopus subject areas

  • Information Systems

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