Entity retrieval via entity factoid hierarchy
Refereed conference paper presented and published in conference proceedings

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AbstractWe propose that entity queries are generated via a two-step process: users first select entity facts that can distinguish target entities from the others; and then choose words to describe each selected fact. Based on this query generation paradigm, we propose a new entity representation model named as entity factoid hierarchy. An entity factoid hierarchy is a tree structure composed of factoid nodes. A factoid node describes one or more facts about the entity in different information granularities. The entity factoid hierarchy is constructed via a factor graph model, and the inference on the factor graph is achieved by a modified variant of Multiple-try Metropolis algorithm. Entity retrieval is performed by decomposing entity queries and computing the query likelihood on the entity factoid hierarchy. Using an array of benchmark datasets, we demonstrate that our proposed framework significantly improves the retrieval performance over existing models.
All Author(s) ListLu C., Lam W., Liao Y.
Name of Conference53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015
Start Date of Conference26/07/2015
End Date of Conference31/07/2015
Place of ConferenceBeijing
Country/Region of ConferenceChina
Detailed descriptionorganized by Association for Computational Linguistics,
Volume Number1
Pages514 - 523
LanguagesEnglish-United Kingdom

Last updated on 2020-06-09 at 00:49