Towards a Domain Analysis Methodology for Collaborative Filtering

Files in This Item:
File Description SizeFormat 
rafter-domainanalysis.pdf119.23 kBAdobe PDFDownload
Title: Towards a Domain Analysis Methodology for Collaborative Filtering
Authors: Rafter, Rachael
Smyth, Barry
Permanent link:
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 filteringInformation
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Status of Item: Not peer reviewed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

Show full item record

Google ScholarTM


This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.