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Erschienen in:
2009 | OriginalPaper | Buchkapitel
A Vector Space Model for Ranking Entities and Its Application to Expert Search
verfasst von : Gianluca Demartini, Julien Gaugaz, Wolfgang Nejdl
Erschienen in: Advances in Information Retrieval
Verlag: Springer Berlin Heidelberg
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Entity Ranking has recently become an important search task in Information Retrieval. The goal is not to find documents matching query terms, but, instead, finding entities. In this paper we propose a formal model to search entities as well as a complete Entity Ranking system, providing examples of its application to the enterprise context. We experimentally evaluate our system on the Expert Search task in order to show how it can be adapted to different scenarios. The results show that combining simple IR techniques we improve of 53% in terms of P@10 over our baseline.