Reranking Collaborative Filtering with Multiple Self-contained Modalities

  • Yue Shi
  • Martha Larson
  • Alan Hanjalic
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6611)

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.

Keywords

Recommender systems collaborative filtering reranking multiple modalities self-contained modalities 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yue Shi
    • 1
  • Martha Larson
    • 1
  • Alan Hanjalic
    • 1
  1. 1.Multimedia Information Retrieval LabDelft University of TechnologyDelftNetherlands

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