TY - GEN
T1 - Academic conference classification according to subjects using topical keyword extraction
AU - Lee, Sue Kyoung
AU - Kim, Kwanho
N1 - Publisher Copyright:
© 2017.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Academic conference classification
KW - Text categorization
KW - Text mining
KW - Topical information extraction
KW - Web contents analysis
UR - http://www.scopus.com/inward/record.url?scp=85040193853&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85040193853
T3 - Proceedings of the International Conferences on Computer Graphics, Visualization, Computer Vision and Image Processing 2017 and Big Data Analytics, Data Mining and Computational Intelligence 2017 - Part of the Multi Conference on Computer Science and Information Systems 2017
SP - 315
EP - 319
BT - Proceedings of the International Conferences on Computer Graphics, Visualization, Computer Vision and Image Processing 2017 and Big Data Analytics, Data Mining and Computational Intelligence 2017 - Part of the Multi Conference on Computer Science and Information Systems 2017
A2 - Rodrigues, Luis
A2 - Xiao, Yingcai
A2 - Abraham, Ajith P.
PB - IADIS
T2 - 11th International Conferences on Computer Graphics, Visualization, Computer Vision and Image Processing, CGVCVIP 2017 and International Conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2017
Y2 - 21 July 2017 through 23 July 2017
ER -