Artículos

 

Evaluación de relaciones ontológicas en corpora de dominio restringido

 

Evaluation of Ontological Relations in Corpora of Restricted Domain

 

Mireya Tovar^1,2, David Pinto², Azucena Montes^1,3, Gabriel González-Serna¹ and Darnes Vilariño²

 

¹ Centro Nacional de Investigación y Desarrollo Tecnológico, Cuernavaca, Morelos, México. mtovar@cenidet.edu.mx, gabriel@cenidet.edu.mx.

² Benemérita Universidad Autónoma de Puebla, Facultad de Ciencias de la Computación, Puebla, México. dpinto@cs.buap.mx, darnes@cs.buap.mx.

³ Universidad Nacional Autónoma de México, Grupo de Ingeniería Lingüística, México. AMontesR@iingen.unam.mx.

Autor de correspondencia es Mireya Tovar.

 

Article received on 20/03/2014.
Accepted on 18/09/2014.

 

Resumen

En este artículo proponemos una evaluación automática de relaciones en ontologías de dominio restringido. En particular, usamos varios patrones léxico sintácticos con la finalidad de evaluar las relaciones class-inclusion y relaciones ontológicas que contiene la ontología. Nuestro enfoque se centra en un corpus de referencia para encontrar evidencia de la validez de la relación. El enfoque es capaz de proporcionar una medida de exactitud para cada ontología evaluada, un valor asociado de alguna manera con la calidad de la relaciones de la ontología. Esta puntuación se da con cierto grado de confiabilidad, obtenida mediante la comparación de los resultados dados por el enfoque contra de la evaluación de expertos humanos y un baseline.

Palabras clave: Evaluación de relaciones, patrones léxico sintácticos, ontologías de dominio restringido.

 

Abstract

In this paper we propose a new approach for automatic evaluation of relations in ontologies of restricted domain. In particular, we use various lexico-syntactic patterns with the aim of evaluating the class-inclusion and ontological relations that the ontology holds. Our approach focuses on a reference corpus for finding evidence of the relation validity. The approach is capable to provide an accuracy measure for each ontology evaluated, a value associated in some way with the quality of the ontology relations. This score is given with a certain degree of reliability, and it is obtained by comparing the results given by our approach against the evaluation of human experts and a baseline.

Keywords: Evaluation of relations, lexico-syntactic patterns, ontologies of restricted domain.

 

DESCARGAR ARTÍCULO EN FORMATO PDF

 

Agradecimientos

Los autores agradecen el apoyo otorgado por la Benemérita Universidad Autónoma de Puebla, México y al Centro Nacional de Investigación y Desarrollo Tecnológico, Campus Cuernavaca, México para la realización de este trabajo de investigación, el cual ha sido parcialmente financiado por el Consejo Nacional de Ciencia y Tecnología (CONACYT) con el número de becario 54371, por el Programa para el Mejoramiento del Profesorado (PROMEP) con folio BUAP-792 y número de convenio PROMEP/103.5/12/4962, y a través del proyecto CONACYT 106625.

 

Referencias

1. Bejar, I., Chaff in, R., & Embretson, S. (1991). Cognitive and Psychometric Analysis of Analogical Problem Solving. Recent Research in Psychology Series. Springer London, Limited.         [ Links ]

2. Bhatt, B. & Bhattacharyya, P. (2012). Domain specific ontology extractor for indian languages. Proceedings of the 10th Workshop on Asian Language Resources, The COLING 2012 Organizing Committee, Mumbai, India, pp. 75-84.         [ Links ]

3. Brank, J., Grobelnik, M., & Mladenic, D. (2005). A survey of ontology evaluation techniques. Proc. of 8th Int. multi-conf. Information Society, pp. 166-169.         [ Links ]

4. Brewster, C., Alani, H., Dasmahapatra, S., & Wilks, Y. (2004). Data driven ontology evaluation. Proceedings of International Conference on Language Resources and Evaluation, pp.         [ Links ]

5. Cantador, I., Fernández, M., & Castells, P. (2006). A collaborative recommendation framework for ontology evaluation and reuse. Actas de International Workshop on Recommender Systems, en la 17th European Conference on Artificial Intelligence (ECAI2006), Riva del Garda, Italia, pp. 67-71.         [ Links ]

6. Cerda L, J. & Villarroel Del P, L. (2008). Evaluación de la concordancia inter-observador en investigación pediátrica: Coeficiente de Kappa. Revista chilena de pediatría, Vol. 79, pp. 54 - 58.         [ Links ]

7. Ciaramita, M., Gangemi, A., Ratsch, E., Saric, J., & Rojas, I. (2005). Unsupervised learning of semantic relations between concepts of a molecular biology ontology. IJCAI, Professional Book Center, pp. 659-664.         [ Links ]

8. Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, Vol. 20, No. 1, pp. 37-46.         [ Links ]

9. de Cea, G. A., de Mon, I. A., & Montiel-Ponsoda, E. (2009). From linguistic patterns to ontology structures. 8th International Conference on Terminology and Artificial Intelligence.         [ Links ]

10. Dellschaft, K. & Staab, S. (2008). Strategies for the evaluation of ontology learning. Buitelaar, P. & Cimiano, P., editors, Bridging the Gap between Text and Knowledge Selected Contributions to Ontology Learning and Population from Text, IOS Press, Amstedam.         [ Links ]

11. Gómez-Pérez, A. (2004). Ontology Evaluation. International Handbooks on Information Systems. Springer.         [ Links ]

12. Grigonyte, G. (2010). Building and Evaluating Domain Ontologies: NLP Contributions. Logos-Verlag.         [ Links ]

13. Gruber, T. R. (1993). Towards Principles for the Design of Ontologies Used for Knowledge Sharing. Guarino, N. & Poli, R., editors, Formal Ontology in Conceptual Analysis and Knowledge Representation, Kluwer Academic Publishers, Deventer, The Netherlands.         [ Links ]

14. Hearst, M. A. (1992). Automatic acquisition of hyponyms from large text corpora. Proceedings of the 14th International Conference on Computational Linguistics, pp. 539-545.         [ Links ]

15. Jacobs, V. (2006). Using the semantics of prepositions for ontology learning. Master's thesis, Utrecht University, the Netherlands.         [ Links ]

16. Jiménez Muñoz, R. J. (2013). Un sistema de búsqueda semántica de información para su uso en el dominio de recuperación mejorada en yacimientos petroleros. Master's thesis, Fac. Ciencias de la Computación, BUAP, Puebla, Mex.         [ Links ]

17. Jurgens, D., Mohammad, S., Turney, P., & Holyoak, K. (2012). Semeval-2012 task 2: Measuring degrees of relational similarity. *SEM 2012: The First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012), Association for Computational Linguistics, Montreal, Canada, pp. 356-364.         [ Links ]

18. Kavalec, M., Maedche, A., & Svatek, V. (2004). Discovery of lexical entries for non-taxonomic relations in ontology learning. van Emde Boas, P., Pokorny, J., Bielikova, M., & Stuller, J., editors, SOFSEM, volume 2932 of Lecture Notes in Computer Science, Springer, pp. 249-256.         [ Links ]

19. Kendall, M. G. (1938). A new measure of rank correlation. Biometrika, Vol. 30, No. 1/2, pp. 81-93.         [ Links ]

20. Klaussner, C. & Zhekova, D. (2011). Lexico-syntactic patterns for automatic ontology building. Proceedings of the Second Student Research Workshop associated with RANLP 2011 , RANLP 2011 Organising Committee, Hissar, Bulgaria, pp. 109-114.         [ Links ]

21. Landis, J. R. & Koch, G. G. (1977). The measurement of ovserver agreement for categorical data. Biometrics, Vol. 33, No. 1, pp. 159-174.         [ Links ]

22. Lovrencic, S. & Mirko, C. (2008). Ontology evaluation - comprising verification and validation. Proceedings of Central European Conference on Information and Intelligent Systems, CECIIS - 2008.         [ Links ]

23. Maedche, A. & Staab, S. (2002). Measuring similarity between ontologies. Proceedings of European Knoeledge Ackquisition Workshop (EKAW), pp.         [ Links ] .

24. Manning, C., Raghavan, P., & Schütze, H. (2008). Introduction to Information Retrieval. An Introduction to Information Retrieval. Cambridge University Press.         [ Links ]

25. Maynard, D., Funk, A., & Peters, W. (2009). Sprat: a tool for automatic semantic pattern-based ontology population. International Conference for Digital Libraries and the Semantic Web.         [ Links ]

26. Mititelu, V. B. (2011). Hyponymy patterns in romanian. Memoirs of the Scientific Sections of the Romanian Academy, Vol. XXXIV, pp. 31-40.         [ Links ]

27. Montiel-Ponsoda, E. & Aguado de Cea, G. (2008). Using natural language patterns forthe development of ontologies. Researching specialized languages, pp. 332-345.         [ Links ]

28. Padro, L. & Stanilovsky, E. (2012). Freeling 3.0: Towards wider multilinguality. Proceedings of the Language Resources and Evaluation Conference (LREC 2012), ELRA, Istanbul, Turkey.         [ Links ]

29. Pak, J. & Zhou, L. (2009). A framework for ontology evaluation. Sharman, R., Rao, H. R., & Raghu, T. S., editors, WEB, volume 52 of Lecture Notes in Business Information Processing, Springer, pp. 1018.         [ Links ]

30. Paslaru, E. (2005). Using context information to improve ontology reuse. Doctoral Workshop at the 17th Conference on Advanced Information Systems Engineering CAiSE05.         [ Links ]

31. Porter, M. F. (1997). Readings in information retrieval. chapter An Algorithm for Suffix Stripping. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, pp. 313-316.         [ Links ]

32. Reyes Ortiz, J. A. (2013). Creación automática de Ontologías a partir de Textos con un Enfoque Linguístico. Ph.D. thesis, Dept Ciencias Computacionales, Cenidet, Cuernavaca, Mor., Mex.         [ Links ]

33. Rios-Alvarado, A. B., Lopez-Arevalo, I., & Sosa, V. J. S. (2013). Learning concept hierarchies from textual resources for ontologies construction. Expert Syst. Appl., Vol. 40, No. 15, pp. 5907-5915.         [ Links ]

34. Ruiz, J. L. J. (2001). Iniciación a la Linguistica. Editorial Club Universitario.         [ Links ]

35. Ruiz-Casado, M., Alfonseca, E., & Castells, P. (2005). Automatic extraction of semantic relationships for wordnet by means of pattern learning from wikipedia. NLDB, Springer Verlag, pp. 67-79.         [ Links ]

36. Sabou, M., Lopez, V., Motta, E., & Uren, V. (2006). Ontology selection: Ontology evaluation on the real semantic web. Proceedings The 4th International EON Workshop, Evaluation of Ontologies for the Web.         [ Links ]

37. Saint-Dizier, P. & Viegas, E. (1995). Computational Lexical Semantics. Studies in Natural Language Processing. Cambridge University Press.         [ Links ]

38. Salem, S. & Abdel Rahman, S. (2010). A multiple-domain ontology builder. Proceedings of the 23rd International Conference on Computational Linguistics, Association for Computational Linguistics, Stroudsburg, PA, USA, pp. 967-975.         [ Links ]

39. Schutz, A. & Buitelaar, P. (2005). Relext: A tool for relation extraction from text in ontology extension. Proceedings of the 4th International Semantic Web Conference (ISWC), pp. 1-5.         [ Links ]

40. Stevenson, M. & Greenwood, M. A. (2005). A semantic approach to ie pattern induction. Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, ACL '05, Association for Computational Linguistics, Stroudsburg, PA, USA, pp. 379-386.         [ Links ]

41. Stevenson, M. & Greenwood, M. A. (2006). Learning Information Extraction Patterns Using Word-Net. Proceedings of the 5th Intl. Conf. on Language Resources and Evaluations (LREC), pp. 95-102.         [ Links ]

42. Tegos, A., Karkaletsis, V., & Potamianos, A. (2008). Learning of semantic relations between ontology concepts using statistical techniques. High-level Information Extraction Workshop 2008 (HLIE08), ECML-PKDD.         [ Links ]

43. Tovar, M., Montes, A., & Pinto, D. (2013). Methodology for automatic evaluation of restricted domain ontologies. Research in Computing Science, Special Issue: Advances in Pattern Recognition, Vol. 61, pp. 63-72.         [ Links ]

44. Volkova, S., Caragea, D., Hsu, W., Drouhard, J., & Fowles, L. (2010). Boosting biomedical entity extraction by using syntactic patterns for semantic relation discovery. Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on, volume 1, pp. 272-278.         [ Links ]

45. Zarrouk, M., Lafourcade, M., & Joubert, A. (2013). Inference and reconciliation in a crowdsourced lexical-semantic network. Computacion y Sistemas, Vol. 17, No. 2, pp. 147-159.         [ Links ]

46. Zavitsanos, E., Paliouras, G., & Vouros, G. A. (2011). Gold standard evaluation of ontology learning methods through ontology transformation and alignment. IEEE Trans. Knowl. Data Eng., Vol. 23, No. 11, pp. 1635-1648.         [ Links ]

47. Zouaq, A., Gasevic, D., & Hatala, M. (2012). Linguistic patterns for information extraction in ontoc-maps. Blomqvist, E., Gangemi, A., Hammar, K., & del Carmen Suarez-Figueroa, M., editors, WOP, volume 929 of CEUR Workshop Proceedings, CEUR-WS.org.         [ Links ]