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General Information
ISSN:
1798-2340 (Online)
Frequency:
Monthly
DOI:
10.12720/jait
Indexing:
ESCI (Web of Science)
,
Scopus
,
CNKI
,
etc
.
Acceptance Rate:
19%
APC:
500 USD
Average Days to Accept:
135 days
Journal Metrics:
Impact Factor 2022: 1.0
3.1
2022
CiteScore
49th percentile
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Editor-in-Chief
Prof. Kin C. Yow
University of Regina, Saskatchewan, Canada
I'm delighted to serve as the Editor-in-Chief of
Journal of Advances in Information Technology
.
JAIT
is intended to reflect new directions of research and report latest advances in information technology. I will do my best to increase the prestige of the journal.
What's New
2024-03-28
Vol. 15, No. 3 has been published online!
2024-02-26
The papers published in Vol. 15, Nos. 1&2 have been registered with Crossref.
2024-02-26
Vol. 15, No. 2 has been published online!
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Published Issues
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2017
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Volume 8, No. 3, August 2017
>
A Data-driven Approach to the Automatic Classification of Korean Poetry
Joo Hyun Nam and Kin Choong Yow
GIST College, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
Abstract—
Automatic classification of text is an increasingly important area of research. It has important applications in virtual assistants and recommender systems. Among the different types of literary works, the poem is one of the most difficult to classify automatically because of the prolific use of metaphors and the short length. In this research, we propose a data-driven approach to automatically classify Korean poems. We use three different methods for finding keywords which can train the classifiers. Our results show that the proposed approach can produce better classification accuracy than using a predefined list of keywords created by a human expert.
Index Terms —
automatic classification, data-driven, poem, text mining, Korean text, keyword extraction
Cite: Joo Hyun Nam and Kin Choong Yow, "A Data-driven Approach to the Automatic Classification of Korean Poetry," Vol. 8, No. 3, pp. 172-176, August, 2017. doi: 10.12720/jait.8.3.172-176
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