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2018 | OriginalPaper | Chapter

Personal Attributes Extraction in Chinese Text Based on Distant-Supervision and LSTM

Authors : Wenxi Yao, Jin Liu, Zehuan Cai

Published in: Advances in Computer Science and Ubiquitous Computing

Publisher: Springer Singapore

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Abstract

In this paper, we proposed a distant-supervision approach to solve the problem of insufficient training corpus for extracting attribute from the unstructured text, by using the wiki infobox information to tag the Wikipedia text to get the training corpus. We consider the extract attribute as the sequence annotation question and use the wiki personal text as the training corpus. The clp-2014 task4 is used as the test corpus to test. The experiment result show that this method can enhance the quality of the attribute extraction.

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Metadata
Title
Personal Attributes Extraction in Chinese Text Based on Distant-Supervision and LSTM
Authors
Wenxi Yao
Jin Liu
Zehuan Cai
Copyright Year
2018
Publisher
Springer Singapore
Book
Advances in Computer Science and Ubiquitous Computing

Print ISBN: 978-981-10-7604-6

Electronic ISBN: 978-981-10-7605-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7605-3_84