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Collaborative recommending using formal concept analysis

delete2006-09-01
delete80
PRE
AI
D
Derek Bridge *
DOI：10.1016/j.knosys.2005.11.017delete
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Abstract

Abstract

En 中文
We show how Formal Concept Analysis (FCA) can be applied to Collaborative Recommenders. FCA is a mathematical method for analysing binary relations. Here we apply it to the relation between users and items in a collaborative recommender system. FCA groups the users and items into concepts, ordered by a concept lattice. We present two new algorithms for finding neighbours in a collaborative recommender. Both use the concept lattice as an index to the recommender's ratings matrix. Our experimental results show a major decrease in the amount of work needed to find neighbours, while guaranteeing no loss of accuracy or coverage. (c) 2006 Elsevier B.V. All rights reserved.
Keywords:
collaborative filtering
recommender systems
Formal Concept Analysis
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Journal

K
Knowledge-Based Systems
IF:
7.6
Papers:
1.2W
Citations:
4.5W

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