Demonstrating social search a la HeyStaks

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Title: Demonstrating social search a la HeyStaks
Authors: Smyth, Barry
Coyle, Maurice
Briggs, Peter
Permanent link: http://hdl.handle.net/10197/2289
Date: Oct-2009
Abstract: For all the success of mainstream search engines there are a number of opportunities for improving on the conventional Web search user experience. In this short paper we consider the default assumption that search is solitary in nature, an isolated interaction between individual user and search engine. We highlight the value of a more collaborative approach to Web search and briefy present a novel add-on for mainstream search engines: HeyStaks (www.heystaks.com). It is designed to provide a more collaborative search experience, one in which recommendation technologies play a central role, by learning from the search experiences of groups of searchers in order to provide targeted recommendations during future search sessions.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Keywords: Search;Social search;Internet;Heystaks
Subject LCSH: Internet searching
Web co-browsing
Recommender systems (Information filtering)
Online social networks
Language: en
Status of Item: Peer reviewed
Conference Details: Presented at the 1st International Workshop on Recommendation-Based Industry Applications at The 3rd ACM Conference on Recommender Systems (RecSys 2009), October 2009, New York, NY, USA.
Appears in Collections:CLARITY Research Collection
Computer Science Research Collection

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