Siersdorfer, S., Sizov, S. and Clough, P. (2007) Know the Right People? Recommender Systems for Web 2.0. In: Hinneburg, A., (ed.) LWA 2007 Workshop Proceedings. Workshop on Knowledge and Experience Management, 24-26 Sep 2007, Halle, Germany. Martin-Luther-University Halle-Wittenberg , 330 - 337. ISBN 978-3-86010-907-6
Abstract
Web 2.0 applications like Flickr, YouTube, or Del.icio.us are increasingly popular online communities for creating, editing and sharing content. However, the rapid increase in size of online communities and the availability of large amounts of shared data make discovering relevant content and finding related users a difficult task. Web 2.0 applications provide a rich set of structures and annotations that can be mined for a variety of purposes. In this paper we propose a formal model to characterize users, items, and annotations in Web 2.0 environments. Based on this model we propose recommendation mechanisms using methods from social network analysis, collaborative filtering, and machine learning. Our objective is to construct collaborative recommender systems that predict the utility of items, users or groups based on the multi-dimensional social environment of a given user.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2007 Martin-Luther-University Halle-Wittenberg. This is an author produced version of a paper subsequently published in LWA 2007 Workshop Proceedings. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 Apr 2014 15:01 |
Last Modified: | 19 Dec 2022 13:26 |
Published Version: | http://www.informatik.uni-trier.de/~ley/db/conf/lw... |
Status: | Published |
Publisher: | Martin-Luther-University Halle-Wittenberg |
Refereed: | Yes |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:78528 |