The information-seeking practices of engineers: searching for documents as well as for people
Information Processing and Management: an International Journal
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
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
Automatic people tagging for expertise profiling in the enterprise
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Analysis of an expert search query log
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Foundations and Trends in Information Retrieval
Finding the right supervisor: expert-finding in a university domain
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop
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The task in expert finding is to identify members of an organisation with relevant expertise on a given topic. Typically, an expert search engine uses evidence from the authors of on-topic documents found in the organisation's intranet by search engines. The search result click-through behaviour of many intranet search engine users provides an additional source of evidence to identify topically-relevant documents, and via document authorship, experts. In this poster, we assess the usefulness of click-through log data for expert finding. We find that ranking authors based solely on the clicks their documents receive is reasonably effective at correctly identifying relevant experts. Moreover, we show that this evidence can successfully be integrated with an existing expert search engine to increase its retrieval effectiveness.