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The Department of Computer Science at the University of Cyprus cordially invites you to the Colloquium entitled:

Recommender Systems: Enabling the Provision of Recommendations from Multiple Domains

 

Speaker: Dr. Antonis Loizou
Affiliation: University of Southampton, UK
Category: Colloquium
Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions)
Date: Wednesday, October 14th, 2009
Time: 15:00-16:00 EET
Host: Yannis Dimopoulos and Marios Dikaiakos ({yannis,mdd} AT cs.ucy.ac.cy)
URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2009.loizou

Abstract:
There has recently been a rapid increase in the commercial use of Recommender System technologies, primarily by online retailers. Such systems appear attractive to retailers, since they can be used to identify any products from their catalogue that can be expected to appear interesting to a particular customer, increasing the amount of purchases made. Thus, they are typically designed under assumptions that an exhaustive index of resources for recommendation is available, and that users can be adequately characterised solely through their interactions with such resources. The objective of my work is to show that by automatically and unobtrusively compiling a profile of user activities, a much more complete user representation can be obtained. Furthermore, resources for recommendation can be dynamically introduced to systems using such profiles, by importing preference data from external communities and social networks, thus enabling the provision of recommendations from multiple domains. A methodology for mapping user profiling elements, as well as the resources available for recommendation to Wikipedia articles has been developed to facilitate comparisons and address the problem of heterogeneity. Hyperlinks between Wikipedia articles are assumed to convey latent semantic relationships between the concepts they describe, and used to construct a graph using articles as nodes and hyperlinks as edges. A Markov chain model is then imposed over the graph, and exploited to drive the recommendation engine.

Short Bio:
A. Loizou received his PhD from the University of Southampton in June 2009, working at the Intelligence, Agents, Multimedia group under the supervision of Dr. Srinandan Dasmahapatra and Prof. Paul H. Lewis. He received his undergraduate degree in Computer Science with Artificial Intelligence also from the University of Southampton in 2005. With a background in Machine Learning and Probabilistic Reasoning, his PhD work has been in the field of Recommender Systems with a particular focus on developing systems that are able to provide recommendations from multiple domains. His research interests also include Semantic Web technologies, Multimedia annotation, Information Retrieval and Data Mining.

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Sponsor: The CS Colloquium Series is supported by a generous donation from Microsoft