Towards a Domain Analysis Methodology for Collaborative Filtering
|Title:||Towards a Domain Analysis Methodology for Collaborative Filtering||Authors:||Rafter, Rachael
|Permanent link:||http://hdl.handle.net/10197/4635||Date:||4-Apr-2001||Abstract:||Collaborative filtering has the ability to make personalised information recommendations in the absence of rich content meta-data, relying instead on collations between the preferences of similar users. However, it depends largely on there being sufficient overlap between the profiles of similar users, and its accuracy is compromised in sparse domains with little profile overlap. We describe an extensive analysis that investigates key domain characteristics that are vital to collaborative filtering. We then explain how knowledge of these characteristics has helped to drive the design of a collaborative recommender system for the JobFinder online recruitment service.||Type of material:||Conference Publication||Keywords:||Collaborative filtering;Information||Language:||en||Status of Item:||Not peer reviewed||Conference Details:||23rd BCS-IRSG European Colloquium on Information Retrieval Research (ECIR 01), Darmstadt, Germany, 4-6 April, 2001|
|Appears in Collections:||Computer Science Research Collection|
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