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.
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Shi, Y., Larson, M., Hanjalic, A. (2011). Reranking Collaborative Filtering with Multiple Self-contained Modalities. In: Clough, P., et al. Advances in Information Retrieval. ECIR 2011. Lecture Notes in Computer Science, vol 6611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20161-5_74
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DOI: https://doi.org/10.1007/978-3-642-20161-5_74
Publisher Name: Springer, Berlin, Heidelberg
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