Title:	ANALYSIS OF KEYWORD EXTRACTION METHOD IN UNSTRUCTURED DATA USING SOCIAL DISASTER INFORMATION
Author(s):	Janghyuk Yim, Jiyoung Kim and Kiyun Yu
ISBN:	978-989-8533-66-1
Editors:	Yingcai Xiao and Ajith P. Abraham
Year:	2017
Edition:	Single
Keywords:	Unstructured data, keywords extraction, Machine learning, Social disaster
Type:	Reflection Paper
First Page:	343
Last Page:	346
Language:	English
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Paper Abstract:	In this paper, we extract keywords necessary for spatial analysis of social disaster using news and social media data, which are unstructured data composed of natural language. Documents are composed of unstructured data which contain a large number of words, and all words do not reflect the important contents of the document. Therefore, it is important to extract important words reflecting the contents of the document. Based on the extracted keywords, a user selects a sentence containing the desired information, and extracts a specific keyword using an algorithm that recognizes patterns involved in recognizing necessary information. As a result, keywords are classified into location, time, and disaster information according to their characteristics.
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