We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Cognitive Functionality based Question Answering System

by Ashish Chandiok, D. K. Chaturvedi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 20
Year of Publication: 2018
Authors: Ashish Chandiok, D. K. Chaturvedi
10.5120/ijca2018916375

Ashish Chandiok, D. K. Chaturvedi . Cognitive Functionality based Question Answering System. International Journal of Computer Applications. 179, 20 ( Feb 2018), 1-6. DOI=10.5120/ijca2018916375

@article{ 10.5120/ijca2018916375,
author = { Ashish Chandiok, D. K. Chaturvedi },
title = { Cognitive Functionality based Question Answering System },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2018 },
volume = { 179 },
number = { 20 },
month = { Feb },
year = { 2018 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number20/28981-2018916375/ },
doi = { 10.5120/ijca2018916375 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:55:55.310678+05:30
%A Ashish Chandiok
%A D. K. Chaturvedi
%T Cognitive Functionality based Question Answering System
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 20
%P 1-6
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Applying cognitive functionality in the artificial system is the prospect of next computing era and is speedily attracting the business and industry. As the volume of information increasing rapidly in the digital world, it also tends to challenge the current search engines to mine more significant and related information in precise and comprehensible manner. A Question Answering (QA) system outdoes the traditional information retrieval search engines in such situations. The paper presents and implements cognitive functionality in question answering systems to mimic human-like performance. The work proposes an architecture which trails human mental and brain like problemsolving procedures to answer questions. An illustration also deliberated and elucidated using a practical implementation and evaluation along with its fundamental cognitive functionality.

References
  1. Asma Ben Abacha and Pierre Zweigenbaum. Means: A medical question-answering system combining nlp techniques and semantic web technologies. Information processing & management, 51(5):570–594, 2015.
  2. Amir H Asiaee, Todd Minning, Prashant Doshi, and Rick L Tarleton. A framework for ontology-based question answering with application to parasite immunology. Journal of biomedical semantics, 6(1):31, 2015.
  3. Abraham Bernstein, Esther Kaufmann, Christian Kaiser, and Christoph Kiefer. Ginseng a guided input natural language search engine for querying ontologies. jena user conference 2006. In In Jena User Conference. Citeseer, 2006.
  4. Eric Brill, Susan Dumais, and Michele Banko. An analysis of the askmsr question-answering system. In Proceedings of the ACL-02 conference on Empirical methods in natural language processing-Volume 10, pages 257–264. Association for Computational Linguistics, 2002.
  5. Elena Cabrio, Julien Cojan, Alessio Palmero Aprosio, Bernardo Magnini, Alberto Lavelli, and Fabien Gandon. Qakis: an open domain qa system based on relational patterns. In International SemanticWeb Conference, ISWC 2012, 2012.
  6. Yonggang Cao, Feifan Liu, Pippa Simpson, Lamont Antieau, Andrew Bennett, James J Cimino, John Ely, and Hong Yu. Askhermes: An online question answering system for complex clinical questions. Journal of biomedical informatics, 44(2):277–288, 2011.
  7. Philipp Cimiano, Peter Haase, and J¨org Heizmann. Porting natural language interfaces between domains: an experimental user study with the orakel system. In Proceedings of the 12th international conference on Intelligent user interfaces, pages 180–189. ACM, 2007.
  8. Oscar Ferr´andez, Rub´en Izquierdo, Sergio Ferr´andez, and Jos´e Luis Vicedo. Addressing ontology-based question answering with collections of user queries. Information Processing & Management, 45(2):175–188, 2009.
  9. S´ebastien Ferr´e. Squall: a controlled natural language as expressive as sparql 1.1. In International Conference on Application of Natural Language to Information Systems, pages 114–125. Springer, 2013.
  10. David A Ferrucci. Introduction to this is watson. IBM Journal of Research and Development, 56(3.4):1–1, 2012.
  11. Ulrich Furbach, Ingo Gl¨ockner, Hermann Helbig, and Bj¨orn Pelzer. Loganswer - a deduction-based question answering system (system description). In Alessandro Armando, Peter Baumgartner, and Gilles Dowek, editors, Automated Reasoning, pages 139–146, Berlin, Heidelberg, 2008. Springer Berlin Heidelberg.
  12. B. F. Green, C. Chomsky, and K. Laughery. Baseball: an automatic question answerer. In In: Proceedings of the Western Joint Computer Conference, pages 219–224, New York: Institute of Radio Engineers, NY, USA, 1961.
  13. Shizhu He, Yuanzhe Zhang, Kang Liu, and Jun Zhao. Casia@ v2: A mln-based question answering system over linked data. In CLEF (Working Notes), pages 1249–1259, 2014.
  14. Aditya Kalyanpur, Branimir K Boguraev, Siddharth Patwardhan, J William Murdock, Adam Lally, Chris Welty, John M Prager, Bonaventura Coppola, Achille Fokoue-Nkoutche, Lei Zhang, et al. Structured data and inference in deepqa. IBM Journal of Research and Development, 56(3.4):10–1, 2012.
  15. Boris Katz, Gary C. Borchardt, and Sue Felshin. Natural language annotations for question answering. In FLAIRS Conference, 2006.
  16. Boris Katz, Sue Felshin, Deniz Yuret, Ali Ibrahim, Julie Qiaojin Lin, Gregory Marton, Alton Jerome McFarland, and Baris Temelkuran. Omnibase: Uniform access to heterogeneous data for question answering. In NLDB, 2002.
  17. Keizo Kawata, Hiroyuki Sakai, and Shigeru Masuyama. Quark: A question and answering system using newspaper corpus as a knowledge source. In NTCIR, 2002.
  18. Jin-Dong Kim and K Bretonnel Cohen. Natural language query processing for sparql generation: A prototype system for snomed ct. In Proceedings of biolink, pages 32–38, 2013.
  19. Vanessa Lopez, Miriam Fern´andez, Enrico Motta, and Nico Stieler. Poweraqua: Supporting users in querying and exploring the semantic web. Semantic Web, 3(3):249–265, 2012.
  20. Vanessa Lopez, Michele Pasin, and Enrico Motta. Aqualog: An ontology-portable question answering system for the semantic web. In European Semantic Web Conference, pages 546–562. Springer, 2005.
  21. Axel-Cyrille Ngonga Ngomo, Lorenz B¨uhmann, Christina Unger, Jens Lehmann, and Daniel Gerber. Sorry, i don’t speak sparql: translating sparql queries into natural language. In Proceedings of the 22nd international conference on World Wide Web, pages 977–988. ACM, 2013.
  22. Eric Nyberg, Robert E Frederking, Teruko Mitamura, Matthew W Bilotti, Kerry Hannan, Laurie Hiyakumoto, Jeongwoo Ko, Frank Lin, Lucian Vlad Lita, Vasco Pedro, et al. Javelin i and ii systems at trec 2005. In TREC, volume 2, page 1, 2005.
  23. Luc Plamondon, Guy Lapalme, and Leila Kosseim. The quantum question answering system. In TREC, 2001.
  24. Camille Pradel, Ollivier Haemmerl´e, and Nathalie Hernandez. Swip: a natural language to sparql interface implemented with sparql. In International Conference on Conceptual Structures, pages 260–274. Springer, 2014.
  25. Ali Ghobadi Tapeh and Maseud Rahgozar. A knowledgebased question answering system for b2c ecommerce. Knowledge-Based Systems, 21(8):946–950, 2008.
  26. Christina Unger, Lorenz B¨uhmann, Jens Lehmann, Axel- Cyrille Ngonga Ngomo, Daniel Gerber, and Philipp Cimiano. Template-based question answering over rdf data. In Proceedings of the 21st international conference on World Wide Web, pages 639–648. ACM, 2012.
  27. Christina Unger and Philipp Cimiano. Pythia: Compositional meaning construction for ontology-based question answering on the semantic web. In International Conference on Application of Natural Language to Information Systems, pages 153– 160. Springer, 2011.
  28. Chong Wang, Miao Xiong, Qi Zhou, and Yong Yu. Panto: A portable natural language interface to ontologies. In European Semantic Web Conference, pages 473–487. Springer, 2007.
  29. William A. Woods. Progress in natural language understanding: an application to lunar geology. In AFIPS National Computer Conference, 1973.
  30. Zhiping Zheng. Answerbus question answering system. In Proceedings of the second international conference on Human Language Technology Research, pages 399–404. Morgan Kaufmann Publishers Inc., 2002.
Index Terms

Computer Science
Information Sciences

Keywords

Cognitive Functionality Question Answering System Natural Language Processing Information Retrieval Information Extraction