Collaborative recommending using formal concept analysis

被引：81

作者：

du Boucher-Ryan, Patrick ^{[1
]}

Bridge, Derek ^{[1
]}

机构：

[1] Natl Univ Ireland Univ Coll Cork, Dept Comp Sci, Cork, Ireland

来源：

KNOWLEDGE-BASED SYSTEMS | 2006年 / 19卷 / 05期

关键词：

collaborative filtering; recommender systems; Formal Concept Analysis;

D O I：

10.1016/j.knosys.2005.11.017

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：309 / 315

页数：7

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