Buzzer : online real-time topical news article and source recommender

Author(s)
Uri
Date Issued
2009-08
Date Available
2009-11-27T14:59:50Z
Abstract
The significant growth of media and user-generated content online has allowed for the widespread adoption of recommender systems due to their proven ability to reduce the workload of a user and personalise
content. In this paper, we describe our prototype system called Buzzer, which harnesses real-time micro-blogging activity, such as Twitter, as the basis for promoting personalised content, such as news articles,
from RSS feeds. We also introduce several new features, that include a technique for recommending community articles from the pooled resources of all system users and also a mechanism for recommending source RSS feeds to which the user does not subscribe.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
Springer
Copyright (Published Version)
Springer-Verlag Berlin Heidelberg 2010
Subject – LCSH
Recommender systems (Information filtering)
Social media
Web personalization
User-generated content
DOI
Web versions
Language
English
Status of Item
Not peer reviewed
Journal
L. Coyle, J. Freyne (ed.s). Artificial Intelligence and Cognitive Science : 20th Irish Conference, AICS 2009 Dublin, Ireland, August 19-21, 2009 : Revised Selected Papers, LNAI 6206
Conference Details
Presentation at the 20th Irish Conference on Artificial Intelligence and Cognitive Science (AICS 09), 19th-21st August 2009, Dublin
ISBN
978-3-642-17079-9
This item is made available under a Creative Commons License
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Owning collection
Computer Science Research Collection
Mapped collections
CLARITY Research Collection