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Semantically Enriched Models for Entity Ranking

Semantically Enriched Models for Entity Ranking

  • Krisztian Balog4 
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  • Open Access
  • First Online: 03 October 2018

  • 19k Accesses

  • 1 Citations

Part of the The Information Retrieval Series book series (INRE,volume 39)

Abstract

Perhaps the most exciting challenge and opportunity in entity retrieval is how to leverage entity-specific properties—attributes, types, and relationships—to improve retrieval performance. In this chapter, we take a departure from purely term-based approaches toward semantically enriched retrieval models. We look at a number of specific entity retrieval tasks that have been studied at various benchmarking campaigns. Specifically, these tasks are ad hoc entity retrieval, list search, related entity finding, and similar entity search. Additionally, we also consider measures of (static) entity importance.

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  1. University of Stavanger, Stavanger, Norway

    Krisztian Balog

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Balog, K. (2018). Semantically Enriched Models for Entity Ranking. In: Entity-Oriented Search. The Information Retrieval Series, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-319-93935-3_4

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