A Case Study of Collaboration and Reputation in Social Web Search.

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Title: A Case Study of Collaboration and Reputation in Social Web Search.
Authors: McNally, Kevin
O'Mahony, Michael P.
Coyle, Maurice
Briggs, Peter
Smyth, Barry
Permanent link: http://hdl.handle.net/10197/3913
Date: Oct-2011
Online since: 2012-11-23T15:42:47Z
Abstract: Although collaborative searching is not supported by mainstream search engines, recent research has high- lighted the inherently collaborative nature of many web search tasks. In this paper, we describe HeyStaks (www.heystaks.com), a collaborative web search framework that is designed to complement mainstream search engines. At search time, HeyStaks learns from the search activities of other users and leverages this information to generate recommendations based on results that others have found relevant for similar searches. The key contribution of this paper is to extend the HeyStaks social search model by considering the search expertise, or reputation, of HeyStaks users and using this information to enhance the result recommendation process. In particular, we propose a reputation model for HeyStaks users that utilises the implicit collaboration events that take place between users as recommendations are made and selected. We describe a live-user trial of HeyStaks that demonstrates the relevance of its core recommendations and the ability of the reputation model to further improve recommendation quality. Our findings indicate that incorporating reputation into the recommendation process further improves the relevance of HeyStaks recommendations by up to 40%.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: ACM
Journal: ACM Transactions on Intelligent Systems and Technology
Volume: 3
Issue: 1
Copyright (published version): 2011 ACM
Keywords: AlgorithmsExperimentationSecurityTrustReputationSocial SearchHeyStaks
Subject LCSH: Web co-browsing
Internet searching
Recommender systems (Information filtering)
Information behavior
DOI: 10.1145/2036264.2036268
Language: en
Status of Item: Peer reviewed
Appears in Collections:CLARITY Research Collection
Computer Science Research Collection

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