Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

AQUA: hybrid architecture for question answering services

AQUA: hybrid architecture for question answering services

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Software — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This study describes AQUA software architecture for question answering services. AQUA has been designed as a hybrid system which can be used as closed-domain and open-domain question answering system. The software platform offers flexibility as incrementally software components can be added. AQUA makes intensive use of ontologies in several parts of the question answering system. An important component of AQUA is the similarity algorithm which is used to find similarities between relations and concepts in a query and classes and properties in ontologies. Furthermore, the authors have modified the similarity algorithms so that they can deal with several opinions of software agents and then combine the evidences found by each of the agent. In addition, uncertainty has been considered as uncertainty is always present when similarity is assessed. Finally, a case of study and an evaluation using academic and bibliographic ontologies from the ontology alignment evaluation initiative is presented.

References

    1. 1)
      • W.F. Clocksin , C.S. Mellish . (1981) Programming in Prolog.
    2. 2)
      • Kwok, C., Etzioni, O., Weld, D.S.: `Scaling question answering to the web', Proc. World Wide Web Conf., 2001, Hong Kong, China, p. 150–161.
    3. 3)
      • Moldovan, D., Harabagiu, S., Pasca, M.: `LASSO: a tool for surfing the answer net', Proc. TREC-8 Conf., 1999.
    4. 4)
      • Riloff, E.: `Automatically generating extracting patterns from untagged text', Proc. 13th National Conf. on Artificial Intelligence, (AAAI-96), 1996, Portland Oregon, USA, p. 1044–1049.
    5. 5)
      • W.G. Lehnert . (1978) The process of question answering.
    6. 6)
      • Nagy, M., Vargas-Vera, M., Motta, E.: `Multi-agent ontology mapping with uncertainty on the semantic web', Proc. Third IEEE Int. Conf. on Intelligent Computer Communication and Processing, 2007, Cluj-Napoca, Romania, p. 49–56.
    7. 7)
      • Hovy, E., Gerber, L., Hermjakob, U., Junk, M., Liu, C.-Y.: `Question answering in Webclopedia', Proc. TREC-9 Conf., 13–16 November 2001, Gaithersburg, Maryland.
    8. 8)
      • Nagy, M., Vargas-Vera, M., Stolarski, P.: `DSSim results for OAEI 2008', Proc. Third Int. Workshop on Ontology Matching, 2008, Germany.
    9. 9)
      • N. Guarino . ONTOSEEK: content-based access to the web. IEEE Intell. Syst. , 3 , 70 - 80
    10. 10)
      • Vargas-Vera, M., Motta, E., Domingue, J.: `An ontology-driven question answering system (AQUA)', KMI-TR-129, Knowledge Media Institute, UK, The Open University 2003.
    11. 11)
      • Celjuska, D.: `Semi-automatic construction of ontologies from text', 2004, Master, Technical University Kosice, Slovakia.
    12. 12)
      • Vargas-Vera, M., Domingue, J., Motta, E., Buckingham Shum, S., Lanzoni, M.: `Knowledge extraction by using an ontology-based annotation tool', Proc. Workshop on Knowledge Markup & Semantic Annotation, Held in Conjunction with the First Int. Conf. Knowledge Capture, (K-CAP 2001), October 2001, Victoria, Canada, p. 5–12.
    13. 13)
      • Vargas-Vera, M., Motta, E., Domingue, J., Lanzoni, M., Stutt, A., Ciravegna, F.: `MnM: ontology driven semi-automatic and automatic support for semantic markup', Proc. 13th Int. Conf. on Knowledge Engineering and Management, (EKAW 2002), 2002, p. 379–391, (LNCS, 2473).
    14. 14)
      • Vargas-Vera, M., Motta, E., Domingue, J.: `AQUA: an ontology-driven question answering system', Proc. AAAI Spring Symp. on New Directions in Question Answering, 24–26 March 2003, CA, USA, p. 53–57, Stanford University.
    15. 15)
      • Ravichandran, D., Hovy, E.: `Learning surface text patterns for a question answering system', Proc. ACL Conf., 2002, Philadelphia, PA, p. 41–47.
    16. 16)
      • Resnik, P., Diab, M.: `Measuring verb similarity', Proc. 22nd Ann. Meeting on Cognitive Science Society, (COGSCI2000), 2000, Philadelphia, USA.
    17. 17)
      • R. Colomo-Palacios , J.M. Gómez-Berbís , A. García-Crespo , I. Puebla Sánchez . Social global repository: using semantics and social web in software projects. Int. J. Knowl. Learn. , 5 , 452 - 464
    18. 18)
      • D. Lin , P. Pantel . Discovery of inference rules for question answering. J. Nat. Lang. Eng. , 4 , 343 - 360
    19. 19)
      • Nagy, M., Vargas-Vera, M., Motta, E.: `Multi agent ontology mapping framework in the AQUA question answering system', Proc. Int. Mexican Conf. on Artificial Intelligence, (MICAI-2005), 2005, Monterrey, Mexico, p. 70–79.
    20. 20)
      • J.W. Lloyd . (1984) Foundations of logic programming.
    21. 21)
      • Vargas-Vera, M., Celjuska, D.: `Ontology-driven event recognition on news stories', KMI-TR-135, Knowledge Media Institute, 2003, UK, The Open University.
    22. 22)
      • Wu, Z., Palmer, M.: `Verb semantics and lexical selection', Proc. 32nd Ann. Meetings of the Association for Computational Linguistics, 1994, Las Cruces, New Mexico, USA, p. 133–138.
    23. 23)
      • Plamondon, L., Lapalme, G., Diro, R., Kosseim, L.: `The QUANTUM question answering system', Proc. TREC-9 Conf., 2001.
    24. 24)
      • R. Studer , Y. Sure , R. Volz . Managing user focused access to distributed knowledge. J. Univ. Comput. Sci. (JUCS) , 6 , 662 - 672
    25. 25)
      • Katz, B.: `From sentence processing to information access on the world wide web', Proc. AAAI Symp. on Natural Language Processing for the World Wide Web, Stanford University, 24–27 March 1997, CA, USA.
    26. 26)
      • P. Resnik . Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language. J. Artif. Intell. Res. (JAIR) , 95 - 130
    27. 27)
      • Nagy, M., Vargas-Vera, M., Motta, E.: `Managing conflicting beliefs with fuzzy trust on the semantic web', Seventh Mexican Int. Conf. on Artificial Intelligence, (MICAI 2008), 2008, Mexico City, p. 827–837.
    28. 28)
      • M. Vargas-Vera , M.D. Lytras . AQUA: a closed-domain question answering system. Special Issue on J. Inf. Syst. Manage. (IMS) , 3 , 217 - 225
    29. 29)
      • Breck, E., House, D., Light, M., Mani, I.: `Question answering from large document collections', Proc. AAAI Fall Symp. on Question Answering Systems, 1999, North Falmouth, MA, USA, p. 26–31.
    30. 30)
      • Budanitsky, A., Hirst, G.: `Semantic distance in WordNet: an experimental, application-oriented evaluation of five measures', Workshop on WordNet and Other Lexical Resources, Proc. Second Meeting of the North American Chapter of the Association for Computational Linguistics, June 2001, Pittsburgh, p. 29–34.
    31. 31)
      • Doan, A., Madhavan, J., Domingos, P., Halevy, A.: `Learning to map between ontologies on the semantic web', Proc. 11th Int. World Wide Web Conf. (WWW2002), 2002, Honolulu, Hawaii, USA, p. 662–673.
    32. 32)
      • Vargas-Vera, M., Motta, E.: `AQUA – ontology-based question answering system', Proc. Third Int. Mexican Conf. on Artificial Intelligence, (MICAI-2004), p. 468–477, in ‘advances in artificial intelligence’, 2004, (LNAI, 2972).
    33. 33)
      • Hastings, P.: `Use of context in an automatic lexical acquisition mechanism', Proc. Workshop on Context in Natural Language of the 14th Int. Join Conf. on Artificial Intelligence, (IJCAI-1995), 1995.
    34. 34)
      • Moreale, E., Vargas-Vera, M.: `Towards a student portal', KMI-TR-136, Knowledge Media Institute, 2003, UK, The Open University.
    35. 35)
      • Hastings, P.: `Automatic acquisition of word meaning from context', 1994, PhD, University of Michigan, Ann Arbor, MI, USA.
    36. 36)
      • Y. Zhang , R. Witte , J. Rilling , V. Haarslev . Ontological approach for the semantic recovery of traceability links between software artefacts. IET Softw. , 3 , 185 - 203
    37. 37)
      • W. Frakes , R. Baeza-Yates . (1992) Information retrieval: data structures & algorithms.
    38. 38)
      • E. Riloff . An empirical study of automated dictionary construction for information extraction in three domains. AI J. , 101 - 134
    39. 39)
      • Resnik, P.: `Using information content to evaluate semantic similarity in a taxonomy', Proc. IJCAI-95, 1995, Montreal, Canada, p. 448–453.
    40. 40)
      • Katz, B.: `Using English for indexing and retrieving', TR 1096, MIT Artificial Intelligence Laboratory, 1988, USA.
    41. 41)
      • Ciravegna, F., Dingli, A., Guthrie, D., Wilks, Y.: `Mining websites using unsupervised adaptive information extraction', Proc. Tenth Conf. on European Chapter of the Association for Computational Linguistic, 2003, Budapest, Hungary.
    42. 42)
      • Duclaye, F., Francois, Y.: `Using the web as a linguistic resource for learning reformulations automatically', Proc. Third Int. Conf. on Language Resources and Evaluation, (LREC'02), May 2002, Las Palmas, Canary Islands, Spain, 2, p. 390–396.
    43. 43)
      • P. Hastings , S. Wermter , E. Riloff , C. Scheler . (1996) Implications of an automatic lexical acquisition mechanism, Connectionist statistical and symbolic approaches to learning for natural language processing.
    44. 44)
      • Hovy, E., Gerber, L., Hermjakob, U., Liu, C.-Y., Ravichandran, D.: `Toward semantics-based answer pinpointing', Proc. DARPA Human Language Technology Conf., (HLT), 2001, Toulouse, France.
    45. 45)
      • R. Colomo-Palacios , A. García-Crespo , J.M. Gómez-Berbís , C. Casado-Lumbreras , P. Soto-Acosta . SemCASS: technical competence assessment within software development teams enabled by semantics. Int. J. Soc. Hum. Comput. , 3 , 232 - 245
    46. 46)
      • G. Shafer . (1976) A mathematical theory of evidence.
    47. 47)
      • Burke, R.D., Hammond, K.J., Kulyukin, V.A., Lytinen, S.L., Tomuro, N., Schoenberg, S.: `Questions answering from frequently-asked question files: experiences with the FAQ finder system', TR-97-05, University of Chicago, Computer Science Department, 1997, Chicago, USA.
    48. 48)
      • Katz, B., Levin, B.: `Exploiting lexical regularities in designing natural language systems', TR 1041, MIT Artificial Intelligence Laboratory, 1988, USA.
    49. 49)
      • J.F. Baldwin , T.P. Martin , B.W. Pilsworth . (1995) Fril – fuzzy and evidential reasoning in artificial intelligence.
    50. 50)
      • Attardi, G., Cisternino, A., Formica, F., Simi, M., Tommasi, A.: `PIQASso: PIsa question answering system', Proc. TREC-9 Conf., November 2001, Gaithersburg, MD, USA, p. 633–641.
    51. 51)
      • A. García-Crespo , R. Colomo-Palacios , J.M. Gómez-Berbís , M. Mencke . BMR: benchmarking metrics recommender for personnel issues in software development projects. Int. J. Comput. Intell. Syst. , 3 , 257 - 267
    52. 52)
      • G.A. Miller , W.G. Charles . Contextual correlates of semantic similarity. Language Cognit. Process. , 1 , 1 - 28
    53. 53)
      • Stojanovic, N., Maedche, A., Staab, S., Studer, R., Sure, Y.: `SEAL – a framework for developing semantic portALs', Proc. First Int. Conf. on Knowledge Capture, K-CAP'01, 22–23 October 2001, Victoria, Canada.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-sen.2010.0053
Loading

Related content

content/journals/10.1049/iet-sen.2010.0053
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address