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Multiagent Approach to Coreference Resolution Based on the Multifactor Similarity in Ontology Population

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Abstract

The multiagent approach to coreference resolution in the process of extracting information from texts in natural languages for ontology population is described. Special class agents corresponding to ontology classes are defined. They analyze the available information in the corresponding ontology instances. The results of this analysis are used for values to instance attribute, for detecting duplicates and equivalents of instances, for fixing coreferential relations, and for determining the weights of information connections used to resolve ambiguities. Coreferences are resolved taking into account a multifactor similarity measure between extracted objects that combines the semantic, context, positional, and grammar similarity measures. The class agents work within the multiagent approach to text analysis aimed at ontology population.

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References

  1. Petasis, G., Karkaletsis, V., Paliouras, G., Krithara, A., and Zavitsanos, E., in Ontology population and enrichment: State of the art, in Knowledge-Driven Multimedia Information Extraction and Ontology Evolution, Paliouras, G., Spyropoulos, C.D., and Tsatsaronis, G., Eds., Berlin: Springer, 2011, pp. 134–166.

  2. Mitkov, R., Anaphora resolution: The state of the art, Technical report, University of Wolverhampton, 1999.

    Google Scholar 

  3. Mitkov, R., Anaphora resolution in: The Oxford handbook of computational linguistics, R. Mitkov, Ed., New York: Oxford Univ. Press, 2003, pp. 266–283.

  4. Elango, P., Coreference resolution: A survey, Technical Report, UW-Madison, 2005.

    Google Scholar 

  5. Prokofyev, R., Tonon, A., Luggen, M., Vouilloz, L., Difallah, D.E., and Cudre-Mauroux, P., SANAPHOR: Ontology-based coreference resolution, in Proceedings of the 14th International Semantic Web Conference, Bethlehem, Penns. 2015, Lect. Notes Comput. Sci, 2015, vol. 9366, pp. 458–473.

    Google Scholar 

  6. Brennan, S.E., Friedman, M.W., and Pollard, C.J., A centering approach to pronouns, in Proceedings of the 25th annual meeting on Association for Computational Linguistics, Stanford, Calif., 1987, pp. 155–162.

    Chapter  Google Scholar 

  7. Carbonell, J.G. and Brown, R.D., Anaphora resolution: A multi-strategy approach in Proceedings of the 12 International Conference on Computational Linguistics, Budapest, 1988, pp. 96–101.

    Chapter  Google Scholar 

  8. Hobbs, J., Resolving pronoun references, in, Readings in Natural Language Processing, Grosz, B.J., Webber, B.L., and Jones, K.S. Eds., San Francisco: Kaufmann, 1986, pp. 339–352.

    Google Scholar 

  9. Wilks, Y., Preference semantics in The Formal Semantics of Natural Language, E. Keenan E., Ed., Cambridge Univ. Press, 1975, pp. 329–348.

    Chapter  Google Scholar 

  10. Grosz, B.J., Weinstein, S., and Joshi, A.K., Centering: A framework for modeling the local coherence of discourse, J. Comput. Linguistics, 1995, vol. 21, no. 2, pp. 203–225.

    Google Scholar 

  11. Kibrik, A.A., Anaphora in Russian narrative discourse: A cognitive calculative account, in Studies in Anaphora, Fox. B., Ed., Amsterdam: Benjamins, 1996, pp. 255–304.

    Chapter  Google Scholar 

  12. Kibrik, A.A., Dobrov, G.B., Khudyakova, M.V., Loukachevitch, N.V., and Pechenyj, A., A corpus-based study of referential choice: multiplicity of factors and machine learning techniques, in Proceedings of the 13th International Conference Cognitive Modeling in Linguistics, Corfu, Greece, 2011, pp. 118–126.

    Google Scholar 

  13. Harabagiu, S.M., Bunescu, R.C., and Maiorano, S.J., Text and Knowledge Mining for Coreference Resolution, in Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language Technologies, Pittsburgh, Penns. 2001, pp. 1–8.

    Google Scholar 

  14. Soon, W.M. and Ng, H.T., and Lim, D.C.Y., A Machine Learning Approach to Coreference Resolution of Noun Phrases, J. Comput. Linguistics, 2001, vol. 27, no. 4, pp. 521–544.

    Article  Google Scholar 

  15. Rich, E. and LuperFoy, S., An architecture for anaphora resolution, in Proceedings of the Second Conference on Applied Natural Language Processing, Austin, Texas, 1988, pp. 18–24.

    Chapter  Google Scholar 

  16. Zhou, G.D. and Su, J., A high-performance coreference resolution system using a constraint-based multiagent strategy, in Proceedings of the 20th International Conference on Computational Linguistics, Geneva, 2004, pp. 522–528.

    Google Scholar 

  17. Kononenko, I.S. and Sidorova, E.A., Language resources in ontology-driven information systems, in Proceedings of the First Russia and Pacific Conference on Computer Technology and Applications, Vladivostok, Russia, 2010, pp. 18–23.

    Google Scholar 

  18. Sidorova, E.A. and Kononenko, I.S., Representation and use of the genre structure of documentation in text processing, in Proceedings of the Science-Intensive Software Workshop, Novosibirsk, Russia, 2009, pp. 248–254.

    Google Scholar 

  19. Garanina, N. and Sidorova, E., Ontology Population as Algebraic Information System Processing Based on Multi-agent Natural Language Text Analysis Algorithms, Program. Comput. Software, 2015, vol. 41, no. 3, pp. 140–148.

    Article  MathSciNet  MATH  Google Scholar 

  20. Garanina, N. and Sidorova, E., Context-dependent lexical and syntactic disambiguation in ontology population, in Proceedings of the 25th International Workshop on Concurrency, Specification and Programming, Rostock, Germany, 2015, pp. 101–112.

    Google Scholar 

  21. Aref, M.M., A multi-agent system for natural language understanding, in Conference on Integration of Knowledge Intensive Multi-Agent Systems, 2003.

    Google Scholar 

  22. Carvalho, A.M.B.R., de Paiva, D.S., Sichman, J.S., da Silva, J.L.T., Wazlawick, R.S., and de Lima, V.L.S., Multi-agent systems for natural language processing, in Proceedings of the II Iberoamerican Workshop on D.A.I. and M.A.S., Toledo, Spain, 1998, pp. 61–69.

    Google Scholar 

  23. Fum, D., Guida, G., and Tasso, C., A distributed multi-agent architecture for natural language processing, in Proceedings of the 12th conference on Computational linguistics (COLING’ 88), 1988, Vol. 2, pp. 812–814.

    Article  Google Scholar 

  24. Tan, P., Steinbach, M., and Kumar, V., Introduction to Data Mining, Pearson, 2005.

    Google Scholar 

  25. Garanina, N., Sidorova, E., Kononenko, I., and Gorlatch, S., Using multiple semantic measures in a framework for coreference resolution in the process of ontology population, Proc. of the 26th International Workshop on CS&P, Warsaw, 2017 (in press).

    Google Scholar 

  26. Lesot, M-J., Rifqi, M., and Benhadda, H. Similarity measures for binary and numerical data: A survey, Int. J. Knowl. Eng. Soft Data Paradigms, 2009, vol. 1, no. 1, pp. 63–84.

    Article  Google Scholar 

  27. Garanina, N.O. and Bodin, E.V., Distributed termination detection by counting agent, Proceedings of the 23nd International Workshop on Concurrency, Specification and Programming, Chemnitz, Germany, 2014, pp. 69–79.

    Google Scholar 

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Authors and Affiliations

  1. Ershov Institute of Information Systems, Siberian Branch, Russian Academy of Sciences, Novosibirsk, 630090, Russia

    N. O. Garanina, E. A. Sidorova & A. S. Seryi

Authors
  1. N. O. Garanina
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  2. E. A. Sidorova
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  3. A. S. Seryi
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Correspondence to N. O. Garanina.

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Original Russian Text © N.O. Garanina, E.A. Sidorova, A.S. Seryi, 2018, published in Programmirovanie, 2018, Vol. 44, No. 1.

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Garanina, N.O., Sidorova, E.A. & Seryi, A.S. Multiagent Approach to Coreference Resolution Based on the Multifactor Similarity in Ontology Population. Program Comput Soft 44, 23–34 (2018). https://doi.org/10.1134/S0361768818010036

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