%0 Conference Paper %1 Smirnova2011 %A Smirnova, Elena %A Balog, Krisztian %B Proceedings of the 33rd European conference on Advances in information retrieval %C Berlin, Heidelberg %D 2011 %I Springer-Verlag %K expert navigation pragmatics tag_hierarchies %P 580--592 %T A user-oriented model for expert finding %U http://dl.acm.org/citation.cfm?id=1996889.1996964 %X Expert finding addresses the problem of retrieving a ranked list of people who are knowledgeable on a given topic. Several models have been proposed to solve this task, but so far these have focused solely on returning the most knowledgeable people as experts on a particular topic. In this paper we argue that in a real-world organizational setting the notion of the "best expert" also depends on the individual user and her needs.We propose a user-oriented approach that balances two factors that influence the user's choice: time to contact an expert, and the knowledge value gained after. We use the distance between the user and an expert in a social network to estimate contact time, and consider various social graphs, based on organizational hierarchy, geographical location, and collaboration, as well as the combination of these. Using a realistic test set, created from interactions of employees with a university-wide expert search engine, we demonstrate substantial improvements over a state-of-the-art baseline on all retrieval measures. %@ 978-3-642-20160-8

@inproceedings{Smirnova2011, abstract = {Expert finding addresses the problem of retrieving a ranked list of people who are knowledgeable on a given topic. Several models have been proposed to solve this task, but so far these have focused solely on returning the most knowledgeable people as experts on a particular topic. In this paper we argue that in a real-world organizational setting the notion of the "best expert" also depends on the individual user and her needs.We propose a user-oriented approach that balances two factors that influence the user's choice: time to contact an expert, and the knowledge value gained after. We use the distance between the user and an expert in a social network to estimate contact time, and consider various social graphs, based on organizational hierarchy, geographical location, and collaboration, as well as the combination of these. Using a realistic test set, created from interactions of employees with a university-wide expert search engine, we demonstrate substantial improvements over a state-of-the-art baseline on all retrieval measures.}, acmid = {1996964}, added-at = {2012-02-20T13:35:03.000+0100}, address = {Berlin, Heidelberg}, author = {Smirnova, Elena and Balog, Krisztian}, biburl = {https://www.bibsonomy.org/bibtex/2b364101973844b8e4674ffa4794db5d0/psinger}, booktitle = {Proceedings of the 33rd European conference on Advances in information retrieval}, description = {A user-oriented model for expert finding}, interhash = {7d3e30773f8209e94238c07cbfc02b4b}, intrahash = {b364101973844b8e4674ffa4794db5d0}, isbn = {978-3-642-20160-8}, keywords = {expert navigation pragmatics tag_hierarchies}, location = {Dublin, Ireland}, numpages = {13}, pages = {580--592}, publisher = {Springer-Verlag}, series = {ECIR'11}, timestamp = {2012-02-20T13:35:03.000+0100}, title = {A user-oriented model for expert finding}, url = {http://dl.acm.org/citation.cfm?id=1996889.1996964}, year = 2011 }