Collaborative recommending using formal concept analysis

  • Patrick Du Boucher-Ryan
  • , Derek Bridge

Research output: Chapter in Book/Report/Conference proceedingsConference proceedingpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationResearch and Development in Intelligent Systems XXII - Proceedings of AI 2005, the 25th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
PublisherSpringer London
Pages205-218
Number of pages14
ISBN (Print)184628225X, 9781846282256
DOIs
Publication statusPublished - 2006
Event25th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2005 - Cambridge, United Kingdom
Duration: 12 Dec 200514 Dec 2005

Publication series

NameResearch and Development in Intelligent Systems XXII - Proceedings of AI 2005, the 25th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence

Conference

Conference25th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2005
Country/TerritoryUnited Kingdom
CityCambridge
Period12/12/0514/12/05

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