Improving context and category matching for entity search

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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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Chen, Y., Gao, L., Shi, S., Du, X., & Wen, J. R. (2014). Improving context and category matching for entity search. In Proceedings of the National Conference on Artificial Intelligence (Vol. 1, pp. 16–22). AI Access Foundation. https://doi.org/10.1609/aaai.v28i1.8711

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