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A SURVEY OF ALGORITHMS AND SYSTEMS FOR EXPERT LOCATION IN SOCIAL NETWORKS

By Theodoros Lappas, Kun Liu and Evimaria Terzi

Abstract

Given a particular task and a set of candidates, one often wants to identify the right expert (or set of experts) that can perform the given task. We call this problem the expert-location problem and we survey its different aspects as they arise in practice. For example, given the activities of candidates within a context (e.g., authoring a document, answering a question), we first describe methods for evaluating the level of expertise for each of them. Often, experts are organized in networks that correspond to social networks or organizational structures of companies. We next devote part of the chapter for describing algorithms that compute the expertise level of individuals by taking into account their position in such a network. Finally, complex tasks often require the collective expertise of more than one experts. In such cases, it is more realistic to require a team of experts that can collaborate towards a common goal. We describe algorithms that identify effective expert teams within a network of experts. The chapter is a survey of different algorithms for expertise evaluation and team identification. We highlight the basic algorithmic problems and give some indicative algorithms that have been developed in the literature. We conclude the chapter by providing a comprehensive overview of real-life systems for expert location.

Topics: Expertise Location, Language Models, Ranking, Propagation, Team Formation C. C. Aggarwal (ed, Social Network Data Analytics, DOI 10.1007/978-1-4419-8462-3_8, © Springer Science+Business Media, LLC 2011216 SOCIAL NETWORK DATA ANALYTICS
Publisher: 2013-10-11
Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.352.3056
Provided by: CiteSeerX
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