Improving Context and Category Matching for Entity Search

Authors

  • Yueguo Chen Renmin University of China
  • Lexi Gao Renmin University of China
  • Shuming Shi Microsoft Research Asia
  • Xiaoyong Du Renmin University of China
  • Ji-Rong Wen Renmin University of China

DOI:

https://doi.org/10.1609/aaai.v28i1.8711

Keywords:

entity search, language model

Abstract

Entity search is to retrieve a ranked list of named entities of target types to a given query. In this paper, we propose an approach of entity search by formalizing both context matching and category matching. In addition, we propose a result re-ranking strategy that can be easily adapted to achieve a hybrid of two context matching strategies. Experiments on the INEX 2009 entity ranking task show that the proposed approach achieves a significant improvement of the entity search performance (xinfAP from 0.27 to 0.39) over the existing solutions.

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Published

2014-06-19

How to Cite

Chen, Y., Gao, L., Shi, S., Du, X., & Wen, J.-R. (2014). Improving Context and Category Matching for Entity Search. Proceedings of the AAAI Conference on Artificial Intelligence, 28(1). https://doi.org/10.1609/aaai.v28i1.8711