A study of selection noise in collaborative web search

Authors:
Oisín Boydell;Barry Smyth;Cathal Gurrin;Alan F. Smeaton
Affiliations:
Adaptive Information Cluster, Smart Media Institute, Department of Computer Science, University College Dublin, Dublin 4, Ireland;Adaptive Information Cluster, Smart Media Institute, Department of Computer Science, University College Dublin, Dublin 4, Ireland;Adaptive Information Cluster, Centre for Digital Video Processing, Dublin City University, Dublin 9, Ireland;Adaptive Information Cluster, Centre for Digital Video Processing, Dublin City University, Dublin 9, Ireland
Venue:
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Year:
2005

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Abstract

Collaborative Web search uses the past search behaviour (queries and selections) of a community of users to promote search results that are relevant to the community. The extent to which these promotions are likely to be relevant depends on how reliably past search behaviour can be captured. We consider this issue by analysing the results of collaborative Web search in circumstances where the behaviour of searchers is unreliable.