Autoentity: automated entity detection from massive text corpora

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2017

Author dc:creator

• He, Wenqi

Contributors dc:contributor

• Han, Jiawei

• Entity detection
• Phrase mining

Statement dc:rights

• Copyright 2017 Wenqi He

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/97395

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/97395