Using Twitter to recommend real-time topical news

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Title: Using Twitter to recommend real-time topical news
Authors: Phelan, Owen
McCarthy, Kevin
Smyth, Barry
Permanent link: http://hdl.handle.net/10197/1893
Date: Oct-2009
Abstract: Recommending news stories to users, based on their preferences,has long been a favourite domain for recommender systems research. In this paper, we describe a novel approach to news recommendation that harnesses real-time micro-blogging activity, from a service such as Twitter, as the basis for promoting news stories from a user's favourite RSS feeds. A preliminary evaluation is carried out on an implementation of this technique that shows promising results.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: ACM
Copyright (published version): 2009 Association for Computing Machinery
Keywords: Content-based recommendationNews recommendationRealtime recommendationSocial recommendationTwitter
Subject LCSH: Recommender systems (Information filtering)
Social media
Real-time data processing
Twitter
DOI: 10.1145/1639714.1639794
Language: en
Status of Item: Peer reviewed
Is part of: Proceedings of the third ACM conference on Recommender systems
Conference Details: Paper presented at the 3rd ACM Conference on Recommender Systems (RecSys 2009), New York City, NY, USA, 22-25 October 2009
Appears in Collections:CLARITY Research Collection
Computer Science Research Collection

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