This paper is published in Volume-7, Issue-3, 2021
Area
Computer Science
Author
Wazhma Ahmadi, Dr. Hanumanthappa J.
Org/Univ
Department of Studies in Computer Science, University of Mysore, Karnataka, India
Keywords
Categorization/Classification, Submission System, Stop Words, Administrator
Citations
IEEE
Wazhma Ahmadi, Dr. Hanumanthappa J.. Automatic categorization of Journal Submission System: An approach based on Cosine Similarity, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Wazhma Ahmadi, Dr. Hanumanthappa J. (2021). Automatic categorization of Journal Submission System: An approach based on Cosine Similarity. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.
MLA
Wazhma Ahmadi, Dr. Hanumanthappa J.. "Automatic categorization of Journal Submission System: An approach based on Cosine Similarity." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.
Wazhma Ahmadi, Dr. Hanumanthappa J.. Automatic categorization of Journal Submission System: An approach based on Cosine Similarity, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Wazhma Ahmadi, Dr. Hanumanthappa J. (2021). Automatic categorization of Journal Submission System: An approach based on Cosine Similarity. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.
MLA
Wazhma Ahmadi, Dr. Hanumanthappa J.. "Automatic categorization of Journal Submission System: An approach based on Cosine Similarity." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.
Abstract
In this paper, we have designed the automatic categorization of electronic journal submission system. Hence, eliminating the manual identification/selection of category and subsequently uploading the paper under that category. The proposed system reads the content, process it, removes the stop words and compares the remaining words with already set aside words for categorization/classification. From the extensive experimentation, it was revealed that the proposed system is robust and eliminates the manual involvement of submission administrator.