Reranking collaborative filtering with multiple self-contained modalities

Authors:
Yue Shi;Martha Larson;Alan Hanjalic
Affiliations:
Multimedia Information Retrieval Lab, Delft University of Technology, Delft, Netherlands;Multimedia Information Retrieval Lab, Delft University of Technology, Delft, Netherlands;Multimedia Information Retrieval Lab, Delft University of Technology, Delft, Netherlands
Venue:
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Year:
2011

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Abstract

A reranking algorithm, Multi-Rerank, is proposed to refine the recommendation list generated by collaborative filtering approaches. Multi-Rerank is capable of capturing multiple self-contained modalities, i.e., item modalities extractable from user-item matrix, to improve recommendation lists. Experimental results indicate that Multi-Rerank is effective for improving various CF approaches and additional benefits can be achieved when reranking with multiple modalities rather than a single modality.