Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
Determining expert profiles (with an application to expert finding)
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A language modeling framework for expert finding
Information Processing and Management: an International Journal
Same places, same things, same people?: mining user similarity on social media
Proceedings of the 2010 ACM conference on Computer supported cooperative work
Contextual factors for finding similar experts
Journal of the American Society for Information Science and Technology
Tool support for technology scouting using online sources
ER'11 Proceedings of the 30th international conference on Advances in conceptual modeling: recent developments and new directions
Similar researcher search in academic environments
Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
Foundations and Trends in Information Retrieval
Finding co-solvers on twitter, with a little help from linked data
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
Ranking experts using author-document-topic graphs
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
Information Technology and Management
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The task of finding people who are experts on a topic has recently received increased attention. We introduce a different expert finding task for which a small number of example experts is given (instead of a natural language query), and the system's task is to return similar experts. We define, compare, and evaluate a number of ways of representing experts, and investigate how the size of theinitial example set affects performance. We show that morefine-grained representations of candidates result in higher performance, and larger sample sets as input lead to improved precision.