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1860799935360794624
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INTELEK Repository
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IEEE Transactions on Magnetics
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Online Access
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https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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2013-05-09 14:34:24
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Restricted Document
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7983
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UniSZA
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[1] D. Damljanovic, M. Agatonovic and H. Cunningham, FREyA: an Interactive Way of Querying Linked Data Using Natural Language”, Proc of the European Semantic Web Conference, 2010. [2] D. Damljanovic, M. Agatonovic and H. Cunningham. “Identification of the Question Focus: Combining Syntactic Analysis and Ontology -based Lookup through the User Interaction”, Proc. of the 7th Language Recourses and Evaluation Conference, 2010. [3] D. L. Lee, H. Chuang and K. Seamons, “Document Ranking and the Vector -Space Model”, IEEE Software, 1997, 67 – 75. [4] H. Doan-Nguyen, K. Leila, “The Problem of Precision in Restricted-Domain Question Answering. Some Proposed Methods of Improvement”, The ACL 2004 Workshop on Question Answering in Restricted Domains, 2004, pp. 8-15. [5] J. J. Rocchio, “Relevance Feedback in Information Retrieval”, In G. Salton (ed.), The Smart Retrieval System: experiments in automatic document processing, Prentice Hall, 1971, pp. 313 –323. [6] L. Pizzato, D. Molla and C. Paris, “Pseudo Relevance Feedback Using Named Entities for Question Answering”, Proc. Australasian Language Technology Workshop, 2006, 83 – 90. [7] M. Diana, P. Wim and L. Yaoyong, “Metrics for evaluation of Ontology -Based Information Extraction”, Proc. Intl. Conference on WWW, May 2006. [8] M.R. Kangavari, S. Ghandchi, M. Golpour, “A New Model for Question Answering Systems”, Journal of World Academy of Science, Engineering and Technology, 2008. [9] N. Rose, T. Lim, P. Saint-Dizier, B. Gay, and R.E. Roxas, "A preliminary study of comparative and evaluative questions for business intelligence", Natural Language Processing, 2009. SNLP '09. Eighth International Symposium, Oct. 2009, pp.35-41, 20-22. [10] O. Fernandez , R. Izquierdo, S. Ferrandez and J. L. Vicedo, “Addressing Ontology-based question answering with collections of user queries”., Journal of Information Processing and Management, vol. 45, issue. 2, March 2009, pp 175-188. [11] R. Baeza-Yates, B. Ribeiro-Neto, Modern Information Retrieval. Harlow: Addison-Wesley, 1999. [12] S. Quarteroni, “Personalized Question Answering”, TAL, Vol 51(1), 2010, 97 – 123. [13] S. Quarteroni and S. Manandhar, “Designing an Interactive Open-Domain Question Answering System”, Journal Language Engineering, Vol. 15(1), 2009, pp. 73 – 95. [14] V. Lopez, V. Uren, E. Motta, and M. Pasin, “AquaLog: An Ontology-driven Question Answering System for Organizational Semantic Intranets”. Journal of Web Semantics, vol. 5, 2007, pp. 72-105.
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3810-01-FH02-FIK-14-00711.pdf
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oai_dc
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https://intelek.unisza.edu.my/intelek/pages/view.php?ref=7983
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7983 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=7983 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Article Journal application/pdf 6 1.6 Adobe Acrobat Pro DC 20 Paper Capture Plug-in IEEE Transactions on Magnetics IEEE Transactions on Magnetics 2013-05-09 14:34:24 3810-01-FH02-FIK-14-00711.pdf UniSZA Private Access A Strategy for Question Interpretation In Question Answering System International Journal of Computer Science and Telecommunications A Question answering (QA) system aims to pull exact and precise answer for Natural Language (NL) question. To extract answer from the text corpus or knowledge base, the QA system has to understand exactly what the question is. Ambiguity may arise when NL question contains modifier term which needs to compare and evaluate its semantic dimension. Therefore, a strategy for an evaluation metrics of the associated modifier term is proposed in this paper. The identified metrics may make possible to regulate using user modeling (UM) and relevance feedback (RF) mechanisms. The performance of the proposed model is evaluated by using the standard information retrieval measurement on the Geoquery datasets. 4 5 38-43 [1] D. Damljanovic, M. Agatonovic and H. Cunningham, FREyA: an Interactive Way of Querying Linked Data Using Natural Language”, Proc of the European Semantic Web Conference, 2010. [2] D. Damljanovic, M. Agatonovic and H. Cunningham. “Identification of the Question Focus: Combining Syntactic Analysis and Ontology -based Lookup through the User Interaction”, Proc. of the 7th Language Recourses and Evaluation Conference, 2010. [3] D. L. Lee, H. Chuang and K. Seamons, “Document Ranking and the Vector -Space Model”, IEEE Software, 1997, 67 – 75. [4] H. Doan-Nguyen, K. Leila, “The Problem of Precision in Restricted-Domain Question Answering. Some Proposed Methods of Improvement”, The ACL 2004 Workshop on Question Answering in Restricted Domains, 2004, pp. 8-15. [5] J. J. Rocchio, “Relevance Feedback in Information Retrieval”, In G. Salton (ed.), The Smart Retrieval System: experiments in automatic document processing, Prentice Hall, 1971, pp. 313 –323. [6] L. Pizzato, D. Molla and C. Paris, “Pseudo Relevance Feedback Using Named Entities for Question Answering”, Proc. Australasian Language Technology Workshop, 2006, 83 – 90. [7] M. Diana, P. Wim and L. Yaoyong, “Metrics for evaluation of Ontology -Based Information Extraction”, Proc. Intl. Conference on WWW, May 2006. [8] M.R. Kangavari, S. Ghandchi, M. Golpour, “A New Model for Question Answering Systems”, Journal of World Academy of Science, Engineering and Technology, 2008. [9] N. Rose, T. Lim, P. Saint-Dizier, B. Gay, and R.E. Roxas, "A preliminary study of comparative and evaluative questions for business intelligence", Natural Language Processing, 2009. SNLP '09. Eighth International Symposium, Oct. 2009, pp.35-41, 20-22. [10] O. Fernandez , R. Izquierdo, S. Ferrandez and J. L. Vicedo, “Addressing Ontology-based question answering with collections of user queries”., Journal of Information Processing and Management, vol. 45, issue. 2, March 2009, pp 175-188. [11] R. Baeza-Yates, B. Ribeiro-Neto, Modern Information Retrieval. Harlow: Addison-Wesley, 1999. [12] S. Quarteroni, “Personalized Question Answering”, TAL, Vol 51(1), 2010, 97 – 123. [13] S. Quarteroni and S. Manandhar, “Designing an Interactive Open-Domain Question Answering System”, Journal Language Engineering, Vol. 15(1), 2009, pp. 73 – 95. [14] V. Lopez, V. Uren, E. Motta, and M. Pasin, “AquaLog: An Ontology-driven Question Answering System for Organizational Semantic Intranets”. Journal of Web Semantics, vol. 5, 2007, pp. 72-105.
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| spellingShingle |
A Strategy for Question Interpretation In Question Answering System
|
| subject |
IEEE Transactions on Magnetics
|
| summary |
A Question answering (QA) system aims to pull exact and precise answer for Natural Language (NL) question. To extract answer from the text corpus or knowledge base, the QA system has to understand exactly what the question is. Ambiguity may arise when NL question contains modifier term which needs to compare and evaluate its semantic dimension. Therefore, a strategy for an evaluation metrics of the associated modifier term is proposed in this paper. The identified metrics may make possible to regulate using user modeling (UM) and relevance feedback (RF) mechanisms. The performance of the proposed model is evaluated by using the standard information retrieval measurement on the Geoquery datasets.
|
| title |
A Strategy for Question Interpretation In Question Answering System
|
| title_full |
A Strategy for Question Interpretation In Question Answering System
|
| title_fullStr |
A Strategy for Question Interpretation In Question Answering System
|
| title_full_unstemmed |
A Strategy for Question Interpretation In Question Answering System
|
| title_short |
A Strategy for Question Interpretation In Question Answering System
|
| title_sort |
strategy for question interpretation in question answering system
|