A Study on Components, Benchmark Criteria and Techniques used in Ontology-based Question Answering Systems
Keywords:
Question Answering, Question Answering Components, Question Answering Systems, QAS Domain, Natural Language, OntologyAbstract
With the massive shift in advancement of technology from early ages to present world, there is record change in techniques related to data storage to data access. Principally, Search Engines aims to provide information relevant to the user needs from huge archive of data storage units adopting Information Retrieval (IR) and Information Extraction (IE)techniques where the retrieved results display the long list of web links concerned with the user’s interest topic and to present the information to the user in human understandable form that can enhance the user experience.
With the introduction of Artificial Intelligence (AI) and Computational Linguistics, the technology era shifted towards Question Answering – the Answer Driven Search. The main aim of QAS is to provide exact answer instead of big pack of words to the user’s query automatically in minimal amount of time. Present QASs are built on state-of-art technology attempting to answer user queries from heterogeneous and scattered data sources like semantic web. The preciseness of answering the questions may be enhanced with the integration of ontological enhanced processing. Ontology-based QAS helps better in identification of query context and query words semantics understanding, thus may satisfy the queries in a better way. Presently there are a number of ontology-based QAS evolved in last twenty years and practically comparing all of them in systematic manner is not possible. Hence, some method is required to compare these ontological QAS. Thus, we focused on some benchmarking criteria and techniques used to differentiate and compare these ontology-based QAS.
Downloads
References
L. Zadeh, "From search engines to question-answering systems - The role of fuzzy logic", Progress in Informatics, no. 1, p. 1, 2005.
L. Zadeh, "From search engines to question-answering systems - The problems of World Knowledge, Relevance, Deduction and Precisiation", 2016.
P. Bhatia, R. Madaan, A. Sharma and A. Dixit, "A Comparison Study of Question Answering Systems", Journal of Network Communications and Emerging Technologies (JNCET), vol. 5, no. 2, pp. 192-198, 2015.
Y. Liu, X. Yi, R. Chen and Y. Song, "A Survey on Frameworks and Methods of Question Answering", 3rd International Conference on Information Science and Control Engineering (ICISCE), 2016.
D. Mollá and J. Vicedo, “Question Answering in Restricted Domains: An Overview”, Computational Linguistics, 33(1), pp.41-61, 2007.
Malla, S., M. J. . Meena, O. . Reddy. R, V. . Mahalakshmi, and A. . Balobaid. “A Study on Fish Classification Techniques Using Convolutional Neural Networks on Highly Challenged Underwater Images”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 10, no. 4, Apr. 2022, pp. 01-09, doi:10.17762/ijritcc.v10i4.5524.
T. Dodiya and S. Jain, "Comparison of Question Answering Systems", in Advances in Intelligent Systems and Computing, 1st ed., Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 99-107, 2013.
"MedQA", Askhermes.org, 2017. [Online]. Available: http://askhermes.org/ MedQA/. [Accessed: 06- Feb- 2017].
"HonQA", Services.hon.ch, 2017. [Online]. Available: http://services.hon.ch/ cgi-bin/QA10/qa.pl. [Accessed: 06- Feb- 2017].
Patil, V. N., & Ingle, D. R. (2022). A Novel Approach for ABO Blood Group Prediction using Fingerprint through Optimized Convolutional Neural Network. International Journal of Intelligent Systems and Applications in Engineering, 10(1), 60–68. https://doi.org/10.18201/ijisae.2022.268
E. M. Voorhees, “The TREC-8 question answering track report”, In Proceedings of TREC-8, pages 77–82, 1999.
A. Bouziane, D. Bouchiha, N. Doumi and M. Malki, "Question Answering Systems: Survey and Trends", Procedia Computer Science, vol. 73, pp. 366-375, 2015.
R. Barskar, G. Ahmed and N. Barskar, "An Approach for Extracting Exact Answers to Question Answering (QA) System for English Sentences", Procedia Engineering, vol. 30, pp. 1187-1194, 2012.
Gill, D. R. . (2022). A Study of Framework of Behavioural Driven Development: Methodologies, Advantages, and Challenges. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 8(2), 09–12. https://doi.org/10.17762/ijfrcsce.v8i2.2068
S. Dongre and S. Lodhi, "A survey of different semantic and ontology based question answering system", International Journal of Advanced Computational Engineering and Networking, vol. 2, no. 9, pp. 69-74, 2014.
L. Mei, "Intelligent Question Answering System of Research Based Ontology on Excellent Courses", Fourth International Conference on Computational and Information Sciences, 2012.
S. Kalaivani, K. Duraiswamy, "Comparison of Question Answering Systems Based on Ontology and Semantic Web in Different Environment", Journal of Computer Science, vol. 8, no. 9, pp. 1407-1413, 2012.
A. Mishra and S. Jain, "A survey on question answering systems with classification", Journal of King Saud University - Computer and Information Sciences, vol. 28, no. 3, pp. 345-361, 2016.
A. Abdi, N. Idris and Z. Ahmad, "QAPD: an ontology-based question answering system in the physics domain", Soft Computing, 2016.
A. M. Moussa, R. Abdel-Kader, “QASYO: A Question Answering System for YAGO Ontology” International Journal of Database Theory and Application, vol. 4, no. 2, pp. 99-112, 2011
M. Midhunlal, M. Gopika, “XMQAS - An Ontology Based Medical Question Answering System”, International Journal of Advanced Research in Computer and Communication Engineering, vol. 5, no. 4, pp. 929-932, 2016
A. Asiaee, T. Minning, P. Doshi and R. Tarleton, "A framework for ontology-based question answering with application to parasite immunology", Journal of Biomedical Semantics, vol. 6, no. 1, 2015.
G. Besbes, H. Baazaoui-Zghal and H. Ghezela, "An Ontology-Driven Visual Question-Answering Framework", 19th International Conference on Information Visualisation, pp. 127-132, 2015.
V. Lopez, V. Uren, E. Motta and M. Pasin, "AquaLog: An ontology-driven question answering system for organizational semantic intranets", Web Semantics: Science, Services and Agents on the World Wide Web, vol. 5, no. 2, pp. 72-105, 2007.
M. Vargas-Vera, E. Motta, "AQUA – Ontology-Based Question Answering System", MICAI 2004: Advances in Artificial Intelligence, pp. 468-477, 2004.
P.M Athira, M. Sreeja and P. C. Reghuraj, "Architecture of an Ontology-Based Domain-Specific Natural Language Question Answering System", International journal of Web & Semantic Technology, vol. 4, no. 4, pp. 31-39, 2013.
Sally Fouad Shady. (2021). Approaches to Teaching a Biomaterials Laboratory Course Online. Journal of Online Engineering Education, 12(1), 01–05. Retrieved from http://onlineengineeringeducation.com/index.php/joee/article/view/43
Wenke Yin, Weiyi Ge and Heng Wang, "CDQA: An ontology-based question answering system for Chinese delicacy", 2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems, 2014.
C. Wang, M. Xiong, Q. Zhou and Y. Yu, "PANTO: A Portable Natural Language Interface to Ontologies", Lecture Notes in Computer Science, pp. 473-487.
A. Singh and N. Tyagi, "Ontology Based Question Answering System", International Journal of Innovative research in Computer and Communication Engineering, vol. 1, no. 10, pp. 2429-2434, 2013.
Harabagiu, S., Moldovan, D., Pasca, M., Mihalcea, R., Surdeanu, M., Bunescu, R., Girju, R., Rus, V., and Morarescu, P. ‘Falcon - Boosting Knowledge for Answer Engines’. In Proceeding of the 9th Text Retrieval Conference (Trec-9), pp.479-488, 2000.
X. Xie, W. Song, L. Liu, C. Du and H. Wang, "Research and implementation of automatic question answering system based on ontology", The 27th Chinese Control and Decision Conference (2015 CCDC), 2015.
A. Asiaee, T. Minning, P. Doshi and R. Tarleton, "A framework for ontology-based question answering with application to parasite immunology", Journal of Biomedical Semantics, vol. 6, no. 1, 2015.
M. Latifi, “Using Natural Language Processing for Question Answering in Closed and Open Domains Majid Latifi,” Unpublished, 2018, doi: 10.13140/RG.2.2.16847.30881
Diefenbach, D., Lopez, V., Singh, K. and Maret, P., “Core techniques of question answering systems over knowledge bases: a survey”, Knowledge and Information Systems, 55(3), pp.529-569, 2017

Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.