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Title:Autoentity: automated entity detection from massive text corpora
Author(s):He, Wenqi
Advisor(s):Han, Jiawei
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):entity detection
phrase mining
Abstract:Entity detection is one of the fundamental tasks in Natural Language Processing and Information Retrieval. Most existing methods rely on human annotated data and hand-crafted linguistic features, which makes it hard to apply the model to an emerging domain. In this paper, we propose a novel automated entity detection framework, called AutoEntity, that performs automated phrase mining to create entity mention candidates and enforces lexico-syntactic rules to select entity mentions from candidates. Our experiments on real-world datasets in different domains and multiple languages have demonstrated the effectiveness and robustness of the proposed method.
Issue Date:2017-04-24
Type:Thesis
URI:http://hdl.handle.net/2142/97395
Rights Information:Copyright 2017 Wenqi He
Date Available in IDEALS:2017-08-10
Date Deposited:2017-05


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