F-GSC, A Flexible Graph-based Subject Classifier for Scientific Articles using Topic Hierarchy

Soumya George¹

1. Dept. of Computer Applications, St. George’s College, Aruvithura, India.

Section:Research Paper, Product Type: Journal-Paper
Vol.10 , Issue.6 , pp.69-80, Dec-2022

Online published on Dec 31, 2022

Copyright © Soumya George . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Subject classification of articles using a topic hierarchy or classifier systems enables scholarly search engines to retrieve relevant articles in a fast and efficient manner. This work proposes a flexible knowledge graph-based topic hierarchy that is so flexible as to add new keywords to it. This is an extension of our previous work, which uses a knowledge graph-based topic hierarchy for the subject classification of scholarly articles based on a sequence-based full-text indexing approach into six levels, including the relevant subjects, categories, areas, disciplines, fields, and keywords. The proposed work is tested for efficiency and reliability using the arXiv dataset.

Key-Words / Index Term :
Scholarly search engine; Knowledge graph; Topic hierarchy; Flexible classifier; Subject classification; Sequence graph

References :
[1] Rous, B, Major update to ACM`s computing classification system. Communications of the ACM, 55(11), 12-12, 2012.
[2] Harris, A. L. Impact factor.
[3] Kang, M., Shin, J. D., & Kim, B., Automatic subject classification of korean journals based on kscd. Indian Journal of Science and Technology, 8(S1), 452-456, 2015.
[4] Soumya George, M. Sudheep Elayidom, T. Santhanakrishnan, Knowledge Graph Based Subject Classification of Scholarly Articles”, Journal of Advanced Research in Dynamical & Control Systems, (JARDCS), Volume. 11, 02-Special Issue, 2019
[5] Sammet, J. E., & Ralston, A,The new (1982) computing reviews classification system—final version. Communications of the ACM, 25(1), 13-25, 1982.
[6] Herrmannova, D., & Knoth, P, An analysis of the microsoft academic graph. D-lib Magazine, 22(9/10), 37, 2016.
[7] Kengeri, R., Seals, C. D., Harley, H. D., Reddy, H. P., & Fox, E. A., Usability study of digital libraries: Acm, ieee-cs, ncstrl, ndltd. International Journal on Digital Libraries, 2(2), 157-169, 1999.
[8] Hammond, T., & Pasin, M, The nature. com Ontologies Portal. In LISC@ ISWC (pp. 2-14), 2015.
[9] Dunne, E., & Hulek, K, Mathematics subject classification 2020. European Mathematical Society Magazine, (115), 5-6,2020.
[10] Waltman, L., & Eck, N. J, A new methodology for constructing a publication level classification system of science. Journal of the Association for Information Science and Technology, 63(12), 2378-2392, 2012.
[11] Archambault, É., Beauchesne, O. H., & Caruso, J,Towards a multilingual, comprehensive and open scientific journal ontology. In Proceedings of the 13th international conference of the international society for scientometrics and informetrics (pp. 66-77). South Africa: Durban, 2011, July
[12] Al-Zaidy, R. A., & Giles, C. L., Extracting Semantic Relations for Scholarly Knowledge Base Construction. In Semantic Computing (ICSC), 2018 IEEE 12th International Conference on (pp. 56-63). IEEE, 2018, January.