Experiments in sparsity reduction: Using clustering in collaborative recommenders

Research output: Chapter in Book/Report/Conference proceedingsChapterpeer-review

Abstract

The high cardinality and sparsity of a collaborative recommender's dataset is a challenge to its efficiency. We generalise an existing clustering technique and apply it to a collaborative recommender's dataset to reduce cardinality and sparsity. We systematically test several variations, exploring the value of partitioning and grouping the data.

Original languageEnglish
Title of host publicationArtificial Intelligence and Cognitive Science - 13th Irish Conference, AICS 2002, Proceedings
EditorsMichael O’Neill, Richard F. E. Sutcliffe, Conor Ryan, Malachy Eaton, Niall J. L. Griffith
PublisherSpringer Verlag
Pages144-149
Number of pages6
ISBN (Electronic)3540441840, 9783540441847
DOIs
Publication statusPublished - 2002
Event13th Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2002 - Limerick, Ireland
Duration: 12 Sep 200213 Sep 2002

Publication series

NameLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2464
ISSN (Print)0302-9743

Conference

Conference13th Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2002
Country/TerritoryIreland
CityLimerick
Period12/09/0213/09/02

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