Improving tag recommendation using social networks

Rae, Adam; Sigurbjörnsson, Börkur and van Zwol, Roelof (2010). Improving tag recommendation using social networks. In: RIAO 2010 : 9th international conference on Adaptivity, Personalization and Fusion of Heterogeneous Information, 27-30 Apr 2010, Paris, France.

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URL:	http://research.yahoo.com/node/3155
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Abstract

In this paper we address the task of recommending additional tags to partially annotated media objects, in our case images. We propose an extendable framework that can recommend tags using a combination of different personalised and collective contexts. We combine information from four contexts: (1) all the photos in the system, (2) a user's own photos, (3) the photos of a user's social contacts, and (4) the photos posted in the groups of which a user is a member. Variants of methods (1) and (2) have been proposed in previous work, but the use of (3) and (4) is novel.
For each of the contexts we use the same probabilistic model and Borda Count based aggregation approach to generate recommendations from different contexts into a unified ranking of recommended tags. We evaluate our system using a large set of real-world data from Flickr. We show that by using personalised contexts we can significantly improve tag recommendation compared to using collective knowledge alone. We also analyse our experimental results to explore the capabilities of our system with respect to a user's social behaviour.

Item Type:	Conference Item
Copyright Holders:	2010 Centre de Hautes Etudes Internationales d�Informatique Documentaire, Paris, France
Funders:	EPSRC CASE Studentship
Keywords:	Flickr; tag recommendation; social networks; personalisation
Academic Unit/Department:	Knowledge Media Institute
Interdisciplinary Research Centre:	Centre for Research in Computing (CRC)
Item ID:	21273
Depositing User:	Adam Rae
Date Deposited:	05 May 2010 11:12
Last Modified:	24 Oct 2012 22:38
URI:	http://oro.open.ac.uk/id/eprint/21273

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