Abstract
In this paper, we present a methodology for designing a Precisiated Natural Language (PNL) based deduction engine for automated Question Answering (QA) systems. QA is one type of information retrieval system, and is regarded as the next advancement beyond keyword-based search engines, as it requires deductive reasoning and use of domain/background knowledge. PNL, as discussed by Zadeh, is one representation of natural language based on constraint-centered semantics, which is convenient for computing with words. We describe a hybrid reasoning engine which supports a “multi-pipe” process flow to handle PNL-based deduction as well as other natural language phrases that do not match PNL protoforms. The resulting process flows in a nested form, from the inner to the outer layers: (a) PNL-based reasoning where all important concepts are pre-defined by fuzzy sets, (b) deduction-based reasoning which enables responses drawn from generated/new knowledge, and (c) key phrase based search when (a) and (b) are not possible. The design allows for two levels of response accuracy improvement over standard search, while retaining a minimum performance level of standard search capabilities.
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Beg, M.M.S., Thint, M., Qin, Z.: Precisiating natural language for a question answering system. Submitted to the 11th World Multi Conf. on Systemics, Cybernetics, and Informatics (2007)
Benamara, F.: Cooperative question answering in restricted domains: the WEBCOOP experiment. In: Proceedings ACL 2004 Workshop on Question Answering in Restricted Domains (2004)
Ceusters, W., Smith, B., Van Mol, M.: Using ontology in query answering systems: scenarios, requirements and challenges. In: Bernardi, R., Moortgat, M. (eds.) Proceedings of the 2nd CoLogNET-ElsNET Symposium, Amsterdam, pp. 5–15 (2003)
Chung, H., Song, Y.-I., Han, K.-S., Yoon, D.-S., Lee, J.-Y., Rim, H.-C., Kim, S.-H.: A practical QA system in restricted domains (2004)
Doan-Nguyen, H., Kosseim, L.: The problem of precision in restricted-domain question-answering: some proposed methods of improvements. In: Proceedings ACL 2004 Workshop on Question Answering in Restricted Domains (2004)
Gospodnetic, O., Hatcher, E.: Lucene in Action. Manning, Greenwich (2004)
Miller, G.: Wordnet: a lexical database. Communications of the ACM 38(11), 39–41 (1995)
Thint, M., Beg, M.M.S., Qin, Z.: PNL-enhanced restricted domain question answering system. Submitted to IEEE-FUZZ, London, UK
Available: http://trec.nist.gov/data/qa.html
Available: http://www.w3.org.org/TR/owl-ref
Tsur, O., de Rijke, M., Sima’an, K.: BioGrapher: biography questions as a restricted domain question answering task. In: Proceedings ACL 2004 Workshop on Question Answering in Restricted Domains (2004)
Zadeh, L.A.: A new direction in AI - toward a computational theory of perceptions. A.I. Magazine (Spring, 2001)
Zadeh, L.A.: From computing with numbers to computing with words − from manipulation of measurements to manipulation of perceptions. Int. J. Appl. Math. Comput. Sci. 12(3), 307–324 (2001)
Zadeh, L.A.: Toward a generalized theory of uncertainty (GTU) − an outline. Information Sciences 172, 1–40 (2005)
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Qin, Z., Thint, M., Sufyan Beg, M.M. (2007). Deduction Engine Design for PNL-Based Question Answering System. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds) Foundations of Fuzzy Logic and Soft Computing. IFSA 2007. Lecture Notes in Computer Science(), vol 4529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72950-1_26
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DOI: https://doi.org/10.1007/978-3-540-72950-1_26
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