Textual Analysis by using Knowledge-based Word Sense Disambiguation Approach
Keywords:
Knowledge-based, Textual Analysis, WordNet, Word Sense Disambiguation,Abstract
Textual analysis had been widely used in the software engineering area. Even though some approaches had been suggested over the time, these approaches encounter number of challenges, especially dealing with information extracted from the text requirement. Most studies had chosen to analyse the text manually in order to overcome this challenge. However, the long and complex text would consume more time. This paper will discuss a framework based on the knowledgebased word sense disambiguation approach, an attempt to improve the knowledge representation. In this approach, WordNet 2.1 would be used as the knowledge source used to identify concepts represented by each word in a text.References
G. Bavota, A. De Lucia, R. Oliveto, F. Palomba, and A. Panichella, “Textual analysis and software quality: challenges and opportunities,” unpublished.
L. Moreno, G. Bavota, S. Haiduc, M. D. Penta, R. Oliveto, B. Russo, and A. Marcus, “Query-based configuration of text retrieval solutions for software engineering tasks,” in Proc. 10th Joint Meeting on Foundations of Software Engineering Conf., 2015, pp. 567-578.
N. Roberto, “A quick tour of word sense disambiguation, induction and related approaches,” in Proc. SOFSEM 2012: Theory and Practice of Computer Science Conf, 2012, pp. 115-129.
E. Agirre, E. Alfonseca, K. Hall, J. Kravalova, M. Pasca, and A. Soroa, “A study on similarity and relatedness using distributional and Wordnet-based approaches,” in Proc. Annual Conference of the North American Chapter of the ACL Conf., 2009, pp. 19-27.
C. F. Baker, and C. Fellbaum, “WordNet and FrameNet as complementary resources for annotation,” in Proc. 3rd Linguistic Annotation Workshop Conf., 2009, pp. 125-129.
F. Fabbrini, M. Fusani, S. Gnesi and G. Lami, “The linguistic approach to the natural language requirements quality: benefit of the use of an automatic tool,” in Proc. 26th Annual NASA Goddard Software Engineering Workshop, 2001, pp. 97-105.
N. Kiyavitskaya, N. Zeni, L. Mich, and D. M. Berry, “Requirements for tools for ambiguity identification and measurement in natural language requirements specifications,” Requirements Engineering, vol. 13, no. 3, pp. 207-239, Sept. 2008.
K. Knight and S. K. Luk, “Building a large-scale knowledge base for machine translation,” AAAI, vol. 94, pp. 773-778, Oct.1994.
C. Fellbaum, WordNet: The Encyclopedia of Applied Linguistics. John Wiley & Sons, Ltd, Nov. 2012.
G. Lami, S. Gnesi, F. Fabbrini, M. Fusani, and G. Trentanni, “An automatic tool for the analysis of natural language requirements,” in Informe técnico, CNR Information Science and Technology Institute, Sept. 2009.
K. Simov, P. Osenova and A. Popov, “Using context information for knowledge-based word sense disambiguation,” in International Conf. Artificial Intelligence: Methodology, Systems, and Applications, Sept. 2016, pp. 130-139.
C. D. Ta and T. P. Thi, “Automatic extraction of semantic relations from text documents,” in International Conf. Future Data and Security Engineering, Nov. 2016, pp. 344-351.
T. Hassan, S. Hassan, M.A. Yar and W. Younas, “Semantic analysis of natural language software requirement,” in 6th International Conf. Innovative Computing Technology (INTECH), Aug. 2016, pp. 459-463.
M. Gaeta, F. Orciuoli, S. Paolozzi, and S. Salerno, “Ontology extraction for knowledge reuse: The e-learning perspective,” IEEE Trans. Systems, Man, and Cybernetics-Part A: Systems and Humans, vol. 44, no. 4, pp. 798-809, Jul. 2011.
S. Prasad, “SRS documentation for Hospital Management System,” Sept 2012. Available at http://www.freestudentprojects.com/ studentprojectreport/project-srs/srs-documentation-for-hospitalmanagement-system/
C. Dinsmoor, M. Mei, B. Wong, A. Agrawal, G. Levene, “Software Requirements Specification (SRS) Lane Management System 2,” 2016, Available at https://pdfs.semanticscholar.org/ce98/ b1bada1186e7b09eeca764dff69c64dee0db.pdf
M. Hwang, C. Choi and P. K. Kim, “Automatic enrichment of semantic relation network and its application to word sense disambiguation,” IEEE Trans. Knowledge and Data Engineering, vol. 23, no. 6, pp. 845- 58, Jun 2011.
Y. Shin, Y. Ahn, H. Kim and S. G. Lee, “Exploiting synonymy to measure semantic similarity of sentences,” in Proc. 9th International Conference on Ubiquitous Information Management and Communication, Jan 2015, pp. 40.
C. Fellbaum, “Wordnet(s)” in Encyclopedia of Language & Linguistics, 2nd ed. vol. 13, Keith Brown. Oxford: Elsevier, 2006, pp. 665-670.
J. Ma, W. Xu, Y. H. Sun, E. Turban, S. Wang and O. Liu, “An ontology-based text-mining method to cluster proposals for research project selection,” IEEE Trans. Systems, Man, and Cybernetics-Part A: Systems and Humans, vol. 42, no. 3, pp. 784-90, May 2012.
C. D. Manning, M. Surdeanu, J. Bauer, J. R. Finkel, S. Bethard, and D. McClosky, “The Stanford CoreNLP natural language processing toolkit,” in Proc. 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations Conf., Jun 2014, pp. 55-60.
A. Arellano, E. Carney and M. A. Austin, “Natural language processing of textual requirements,” in Proc.10th International Conference on Systems (ICONS 2015), Apr. 2015, pp. 93-97.
G. Génova, J. M. Fuentes, J. Llorens, O. Hurtado and V. Moreno, “A framework to measure and improve the quality of textual requirements,” Requirements Engineering, vol. 18, no. 1, pp. 25-41, Mar. 2013.
W. Lu, Y. Cai, X. Che and Y. Lu, “Joint semantic similarity assessment with raw corpus and structured ontology for semantic-oriented service discovery,” Personal and Ubiquitous Computing, vol. 20, no. 3, pp. 311-323, Jun. 2016.
F. Sclano and F. Velardi,”Term extractor: A web application to learn the shared terminology of emergent web communities,” in Proc. 3rd International Conference I-ESA, Mar. 2007, pp. 289-290.
Downloads
Published
How to Cite
Issue
Section
License
TRANSFER OF COPYRIGHT AGREEMENT
The manuscript is herewith submitted for publication in the Journal of Telecommunication, Electronic and Computer Engineering (JTEC). It has not been published before, and it is not under consideration for publication in any other journals. It contains no material that is scandalous, obscene, libelous or otherwise contrary to law. When the manuscript is accepted for publication, I, as the author, hereby agree to transfer to JTEC, all rights including those pertaining to electronic forms and transmissions, under existing copyright laws, except for the following, which the author(s) specifically retain(s):
- All proprietary right other than copyright, such as patent rights
- The right to make further copies of all or part of the published article for my use in classroom teaching
- The right to reuse all or part of this manuscript in a compilation of my own works or in a textbook of which I am the author; and
- The right to make copies of the published work for internal distribution within the institution that employs me
I agree that copies made under these circumstances will continue to carry the copyright notice that appears in the original published work. I agree to inform my co-authors, if any, of the above terms. I certify that I have obtained written permission for the use of text, tables, and/or illustrations from any copyrighted source(s), and I agree to supply such written permission(s) to JTEC upon request.