On using the real-time web for news recommendation & discovery

DSpace/Manakin Repository

Show simple item record

dc.contributor.author Phelan, Owen
dc.contributor.author McCarthy, Kevin
dc.contributor.author Bennett, Mike
dc.contributor.author Smyth, Barry
dc.date.accessioned 2011-05-26T11:44:12Z
dc.date.available 2011-05-26T11:44:12Z
dc.date.copyright 2011 The authors en
dc.date.issued 2011-03-28
dc.identifier.isbn 978-1-4503-0637-9
dc.identifier.uri http://hdl.handle.net/10197/2954
dc.description Presented at the 20th International World Wide Web Conference, WWW 2011, Hyderabad, India, March 28 - April 1, 2011 en
dc.description.abstract In this work we propose that the high volumes of data on real-time networks like Twitter can be harnessed as a useful source of recommendation knowledge. We describe Buzzer, a news recommendation system that is capable of adapting to the conversations that are taking place on Twitter. Buzzer uses a content-based approach to ranking RSS news stories by mining trending terms from both the public Twitter timeline and from the timeline of tweets generated by a user’s own social graph (friends and followers). We also describe the result of a live-user trial which demonstrates how these ranking strategies can add value to conventional RSS ranking techniques, which are largely recency-based. en
dc.description.sponsorship Science Foundation Ireland en
dc.description.uri Conference details en
dc.description.uri http://www.www2011india.com/ en
dc.format.extent 526456 bytes
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher ACM en
dc.relation.ispartof WWW '11 Proceedings of the 20th international conference companion on World wide web en
dc.relation.requires CLARITY Research Collection en
dc.rights This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 20th international conference companion on World wide web available at http://doi.acm.org/10.1145/1963192.1963245 en
dc.subject Social recommendation en
dc.subject News recommendation en
dc.subject Content-based recommendation en
dc.subject Realtime recommendation en
dc.subject Twitter en
dc.subject.lcsh Recommender systems (Information filtering) en
dc.subject.lcsh Web 2.0 en
dc.subject.lcsh Social media en
dc.subject.lcsh Web personalization en
dc.subject.lcsh Twitter en
dc.title On using the real-time web for news recommendation & discovery en
dc.type Conference Publication en
dc.internal.availability Full text available en
dc.internal.webversions Publisher's version en
dc.internal.webversions http://dx.doi.org/10.1145/1963192.1963245 en
dc.status Peer reviewed en
dc.identifier.doi 10.1145/1963192.1963245
dc.neeo.contributor Phelan|Owen|aut| en
dc.neeo.contributor McCarthy|Kevin|aut| en
dc.neeo.contributor Bennett|Mike|aut| en
dc.neeo.contributor Smyth|Barry|aut| en


Files in this item

Name: p103.pdf
Size: 514.1Kb
Format: PDF
Download

This item appears in the following Collection(s)

Show simple item record

This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.

If you are a publisher or author and have copyright concerns for any item, please email research.repository@ucd.ie and the item will be withdrawn immediately. The author or person responsible for depositing the article will be contacted within one business day.

Search Research Repository


Advanced Search

Browse