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Abstract: Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative Filtering (CF) is a succesful recommendation technique. User ratings are not expected to be independent, as users follow trends of similar rating behavior. In terms of Text Mining, this is analogous to the formation of higher-level concepts from plain terms. In this paper, we propose a novel CF algorithm which uses Latent Semantic Indexing (LSI) to detect rating ... (Update)
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BibTeX entry: (Update)
@misc{ alexandros-collaborative,
author = "Panagiotis Symeonidis Alexandros",
title = "Collaborative Filtering based on User Trends",
url = "citeseer.ist.psu.edu/761696.html" }
Citations (may not include all citations):226 Using collaborative filtering to weave an information tapest.. (context) - Goldberg, Nichols et al. - 1992 ACM DBLP
192 Using linear algebra for intelligent information retrieval - Berry, Dumais et al. - 1994 ACM
50 Application of dimensionality reduction in recommender syste.. - Sarwar, Karypis et al. - 2000
28 Information retrieval using a singular value decomposition m.. (context) - Furnas, Deerwester et al. - 1988 ACM DBLP
4 A collaborative filtering algorithm and evaluation metric th.. (context) - McLauglin, Herlocher - 2004 ACM
1 GrouplensAn open architecture for collaborative filtering on.. (context) - Resnick, Iacovou et al. - 1994
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