The information-seeking practices of engineers: searching for documents as well as for people
Information Processing and Management: an International Journal
Formal models for expert finding in enterprise corpora
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Voting for candidates: adapting data fusion techniques for an expert search task
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Frequentist and bayesian approach to information retrieval
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Expertise drift and query expansion in expert search
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Voting techniques for expert search
Knowledge and Information Systems
A Vector Space Model for Ranking Entities and Its Application to Expert Search
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
High quality expertise evidence for expert search
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Modeling documents as mixtures of persons for expert finding
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Expert search evaluation by supporting documents
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Hashtag retrieval in a microblogging environment
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Hypergeometric language models for republished article finding
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Phrase pair classification for identifying subtopics
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Foundations and Trends in Information Retrieval
Aggregating evidence from hospital departments to improve medical records search
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
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In Enterprise settings, expert search is considered an important task. In this search task, the user has a need for expertise - for instance, they require assistance from someone about a topic of interest. An expert search system assists users with their "expertise need" by suggesting people with relevant expertise to the topic of interest. In this work, we apply an expert search approach that does not explicitly rank candidates in response to a query, but instead implicitly ranks candidates by taking into account a ranking of document with respect to the query topic. Pseudo-relevance feedback, aka query expansion, has been shown to improve retrieval performance in adhoc search tasks. In this work, we investigate to which extent query expansion can be applied in an expert search task to improve the accuracy of the generated ranking of candidates. We define two approaches for query expansion, one based on the initial of ranking of documents for the query topic. The second approach is based on the final ranking of candidates. The aims of this paper are two-fold. Firstly, to determine if query expansion can be successfully applied in the expert search task, and secondly, to ascertain if either of the two forms of query expansion can provide robust, improved retrieval performance. We perform a thorough evaluation contrasting the two query expansion approaches in the context of the TREC 2005 and 2006 Enterprise tracks.