Title:	ACADEMIC CONFERENCE CLASSIFICATION ACCORDING TO SUBJECTS USING TOPICAL KEYWORD EXTRACTION
Author(s):	Sue Kyoung Lee and Kwanho Kim
ISBN:	978-989-8533-66-1
Editors:	Yingcai Xiao and Ajith P. Abraham
Year:	2017
Edition:	Single
Keywords:	Academic conference classification, Topical information extraction, Text mining, Text categorization, Web contents analysis
Type:	Short Paper
First Page:	315
Last Page:	319
Language:	English
Cover:
Full Contents:	click to dowload
Paper Abstract:	The automatic classification of academic conference information according to research subjects enables researchers to search related academic conference efficiently. Information provided by most conference listing services is limited on title, date, location, and website URL. However, among these features, the only feature containing topical words is title, which causes information insufficient problem. Therefore, we propose methods that aim to resolve the lack of information by utilizing an web contents. Specifically, the proposed methods extract the main contents from a HTML document crawled through the website URL. Based on the similarity between the title of a conference and its main contents, the topical keywords are selected to enforce the important keywords among the main contents. Experiment results show that the use of important keywords based on websites by using the proposed method is successfully to improve the performances of classification for academic conference information.
	Go Back