Refining user and item profiles based on multidimensional data for top-n item recommendation

Tang, Xiaoyu, Xu, Yue, & Geva, Shlomo (2014) Refining user and item profiles based on multidimensional data for top-n item recommendation. In Indrawan-Santiago, Maria, Steinbauer, Matthias, Nguyen, Hong-Quang, Tjoa, A. Min, Khalil, Ismail, & Anderst-Kotsis, Gabriele (Eds.) Proceedings of the 16th International Conference on Information Integration and Web-based Applications & Services (iiWAS '14), ACM, Hanoi, Vietnam, pp. 310-319.

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In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for Collaborative Filtering (CF) item recommendation on multidimensional data. We further present incremental profiling method for updating the profiles. For item recommendation, we seek to delve into different types of relations in data to understand the interaction between users and items more fully, and propose three multidimensional CF recommendation approaches for top-N item recommendations based on the proposed user/item profiles. The proposed multidimensional CF approaches are capable of incorporating not only localized relations of user-user and/or item-item neighbourhoods but also latent interaction between all dimensions of the data. Experimental results show significant improvements in terms of recommendation accuracy.

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ID Code: 82474
Item Type: Conference Paper
Refereed: Yes
Keywords: Multidimensional data, Neighbourhood, Dimensionality reduction, Collaborative filtering, Recommender systems
DOI: 10.1145/2684200.2684284
ISBN: 9781450330015
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 ACM
Deposited On: 13 Mar 2015 00:09
Last Modified: 18 Mar 2015 09:21

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