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Analysis of Some Database Schemas Used to Evaluate Natural Language Interfaces to Databases

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Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

Abstract

Most research work about the development of Natural Language Interface to Databases (NLIDB) has been focused on the study of the interpretation and translation from natural language queries to SQL queries. For this purpose and in order to improve the performance in a NLIDB, researchers have addressed different issues related to natural language processing. In addition to this, we consider that the performance of a NLIDB also depends on its ability to adapt to a database schema. For this reason, we analyzed the Geobase, ATIS and Northwind database schemas, commonly used to evaluate NLIDBs. As a result of this analysis, we present in this paper some issues arising from the three database schemas analyzed, which they should be considered in the implementation of a NLIDB to improve its performance.

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References

  1. Bates, M.: Rapid porting of the parlance natural language interface. In: Proceedings of the workshop on Speech and Natural Language (pp. 83–88). Association for Computational Linguistics. (1989)

    Google Scholar 

  2. Bernstein, A., Kaufmann, E., Kaiser, C.: Querying the semantic web with Ginseng: a guided input natural language search engine. In: 15th workshop on information technologies and systems (WITS 2005), Las Vegas, NV. (2005)

    Google Scholar 

  3. Bobrow, R.J., Resnik, P., Weischedel, R.M.: Multiple underlying systems: translating user request into programs to produce answers. In: Proceedings of the 28th annual meeting of ACL, Pittsburgh, pp. 227–234. (1990)

    Google Scholar 

  4. Buraga, S.C., Cojocaru, L., Nichifor, O.C.: Survey on web ontology editing tools, transactions on automatic control and computer science, Romania, pp. 1–6. (2006)

    Google Scholar 

  5. Chandra, Y.: Natural language interfaces to databases. Doctoral dissertation, University of North Texas. (2006)

    Google Scholar 

  6. Cimiano, P., Haase, P., Heizmann, J.: 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, Honolulu, Hawaii, pp. 180–190. (2007)

    Google Scholar 

  7. Damljanovic, D., Agatonovic, M. Cunningham, H.: Natural language interfaces to ontologies: combining syntactic analysis and ontology-based lookup through the user interaction. In: Proceedings of the 7th extended semantic web conference (ESWC 2010). Springer, Heraklion (2010)

    Google Scholar 

  8. ELF software (English Language Frontend), “Demo Gallery”, http://www.elfsoft.com/help/accelf/overview.htm. (2002)

  9. ELF software (English Language Frontend), “GeoQuery Example”, http://www.elfsoft.com/GeoQuery.htm. (2012)

  10. Ge, R., Mooney, R.J.: A statistical semantic parser that integrates syntax and semantics. In: Proceedings of the ninth conference on computational natural language learning, pp. 9–16. (2005)

    Google Scholar 

  11. Giordani, A., Moschitti, A.: Semantic mapping between natural language questions and SQL queries via syntactic pairing. In: Natural language processing and information systems, pp. 207–221. Springer, Berlin (2010)

    Google Scholar 

  12. Green, Jr., B.F., Wolf, A.K., Chomsky, C., Laughery, K.: Baseball: an automatic question-answerer. In: Papers presented at the May 9–11, 1961, western joint IRE-AIEE-ACM computer conference, pp. 219–224. ACM (1961)

    Google Scholar 

  13. Grosz, B.J., Appelt, D.E., Martin, P.A., Pereira, F.C.: TEAM: an experiment in the design of transportable natural-language interfaces. Artif. Intell. 32(2), 173–243 (1987)

    Article  Google Scholar 

  14. Hendrix, G.G., Sacerdoti, E.D., Sagalowicz, D., Slocum, J.: Developing a natural language interface to complex data. ACM Trans. Database Syst. (TODS) 3(2), 105–147 (1978)

    Article  Google Scholar 

  15. Kate, R.J., Mooney, R.J.: Using string-kernels for learning semantic parsers. In Proceedings of the 21st international conference on computational linguistics and the 44th annual meeting of the association for computational linguistics, pp. 913–920. Association for Computational Linguistics (2006)

    Google Scholar 

  16. Kaufmann, E., Bernstein, A., Zumstein, R.: Querix: a natural language interface to query ontologies based on clarification dialogs. In: 5th international semantic web conference (ISWC 2006), pp. 980–981 (2006)

    Google Scholar 

  17. Kaufmann, E., Bernstein, A., Fischer, L.: NLP-Reduce: a naïve but Domain-independent natural language interface for querying ontologies. In: 4th European semantic web conference (ESWC 2007), Innsbruck, A (2007)

    Google Scholar 

  18. Kubala, F., Barry, C., Bates, M., Bobrow, R., Fung, P., Ingria, R., Stallard, D.: BBN Byblos and HARC February 1992 ATIS benchmark results. In: Proceedings of the workshop on speech and natural language, pp. 72–77. Association for Computational Linguistics (1992)

    Google Scholar 

  19. Microsoft TechNet., chapter 32-English Query Best Practices. www.microsoft.com/technet/prodtechnol/sql/2000/reskit/part9/c3261.mspx?mfr=true

  20. Minock, M., Olofsson, P., Näslund, A.: Towards building robust natural language interfaces to databases. In: Natural language and information systems, pp. 187–198. Springer, Berlin (2008)

    Google Scholar 

  21. Murveit, H., et al.: SRI’s speech and natural language evaluation (in this Proceedings)

    Google Scholar 

  22. Official Airline Guides, Official Airline Guide, North American Edition with Fares, Oakbrook, Illinois, Volume 16, No. 7, January 1, 1990

    Google Scholar 

  23. Popescu, A.: Modern natural language interfaces to databases: composing statistical parsing with semantic tractability. University of Washington (2004)

    Google Scholar 

  24. Seneff, S., et al.: Development and Preliminary Evaluation of the M1T ATIS System (in this Proceedings)

    Google Scholar 

  25. Stratica, N.: Using semantic templates for a natural language interface to the CINDI virtual library. Data Knowledge Eng, 55, 4–19 (2005). doi:10.1016/j.datak.2004.12.002. (Elsevier Science Publishers, The Netherlands)

  26. Tang, L.R., Mooney, R.J.: Using multiple clause constructors in inductive logic programming for semantic parsing. In: Machine learning: ECML 2001, pp. 466–477. Springer, Berlin (2001)

    Google Scholar 

  27. Technology, Linguistic: English Wizard—Dictionary Administrator’s Guide. Linguistic Technology Corp, Littleton (1997)

    Google Scholar 

  28. Thompson, C.A., Mooney, R.J.: Acquiring word-meaning mappings for natural language interfaces. J. Artif. Intell. Res. 18(1), 1–44 (2003)

    MATH  Google Scholar 

  29. Tzoukermann, E.: The use of a commercial natural language interface in the ATIS task. In: HLT (1991)

    Google Scholar 

  30. Wang, C., Xiong, M. Zhou, Q.: PANTO: a portable natural language interface to ontologies. Lecture notes in computer science, vol. 4519/2007, pp. 473–487 (2007)

    Google Scholar 

  31. Ward, W.: Current status of the CMU ATIS System (in this Proceedings)

    Google Scholar 

  32. Warren, D.H.: Efficient processing of interactive relational data base queries expressed in logic. In: Proceedings of the seventh international conference on very large data bases, vol. 7, pp. 272–281. VLDB Endowment (1981)

    Google Scholar 

  33. Wong, Y.W., Mooney, R.J.: Learning for semantic parsing with statistical machine translation. In: Proceedings of human language technology conference/North American chapter of the association for computational linguistics annual meeting, pp. 439–446 (2006)

    Google Scholar 

  34. Woods, W., Kaplan, R., Webber, B.: The Lunar Sciences Natural Language Information System. Bolt Beranek and Newman Inc., Cambridge, Massachusetts Final Report. B. B. N. Report No 2378 (1972)

    Google Scholar 

  35. Zelle, J.M., Mooney, R.J.: Learning to parse database queries using inductive logic programming. In: Proceedings of the thirteenth national conference on artificial intelligence, pp. 1050–1055 (1996)

    Google Scholar 

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Correspondence to Rodolfo A. Pazos R. .

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Florencia-Juárez, R., González B., J.J., Pazos R., R.A., Martínez F., J.A., Morales-Rodríguez, M.L. (2015). Analysis of Some Database Schemas Used to Evaluate Natural Language Interfaces to Databases. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization. Studies in Computational Intelligence, vol 601. Springer, Cham. https://doi.org/10.1007/978-3-319-17747-2_42

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  • DOI: https://doi.org/10.1007/978-3-319-17747-2_42

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