A Generative Language Modeling Approach for Ranking Entities

Authors:
Wouter Weerkamp;Krisztian Balog;Edgar Meij
Affiliations:
ISLA, University of Amsterdam, Amsterdam, The Netherlands 1098XG;ISLA, University of Amsterdam, Amsterdam, The Netherlands 1098XG;ISLA, University of Amsterdam, Amsterdam, The Netherlands 1098XG
Venue:
Advances in Focused Retrieval
Year:
2009

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Abstract

We describe our participation in the INEX 2008 Entity Ranking track. We develop a generative language modeling approach for the entity ranking and list completion tasks. Our framework comprises the following components: (i) entity and (ii) query language models, (iii) entity prior, (iv) the probability of an entity for a given category, and (v) the probability of an entity given another entity. We explore various ways of estimating these components, and report on our results. We find that improving the estimation of these components has very positive effects on performance, yet, there is room for further improvements.