Abstract
Entity ranking on Web scale datasets is still an open challenge. Several resources, as for example Wikipedia-based ontologies, can be used to improve the quality of the entity ranking produced by a system. In this paper we focus on the Wikipedia corpus and propose algorithms for finding entities based on query relaxation using category information. The main contribution is a methodology for expanding the user query by exploiting the semantic structure of the dataset. Our approach focuses on constructing queries using not only keywords from the topic, but also information about relevant categories. This is done leveraging on a highly accurate ontology which is matched to the character strings of the topic. The evaluation is performed using the INEX 2007 Wikipedia collection and entity ranking topics. The results show that our approach performs effectively, especially for early precision metrics.
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Demartini, G., Firan, C.S., Iofciu, T. (2008). L3S at INEX 2007: Query Expansion for Entity Ranking Using a Highly Accurate Ontology. In: Fuhr, N., Kamps, J., Lalmas, M., Trotman, A. (eds) Focused Access to XML Documents. INEX 2007. Lecture Notes in Computer Science, vol 4862. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85902-4_23
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DOI: https://doi.org/10.1007/978-3-540-85902-4_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85901-7
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