Abstract
Pattern-based approaches for knowledge identification in texts assume that linguistic regularities always characterise the same kind of knowledge, such as semantic relations. We report the experimental evaluation of a large set of patterns using an ontology enrichment tool: Camélé on. Results underline the strong corpus influence on the patterns efficiency and on their meaning. This influence confirms two of the hypotheses that motivated to define Camélé on as a support used in a supervised process: (1) patterns and relations must be adapted to each project; (2) human interpretation is required to decide how to report in the ontology the pieces of knowledge identified with patterns.
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Aussenac-Gilles, N., Biébow, B., Szulman, S.: Revisiting Ontology Design: A Method Based on Corpus Analysis. In: Dieng, R., Corby, O. (eds.) EKAW 2000. LNCS (LNAI), vol. 1937, pp. 172–188. Springer, Heidelberg (2000)
Aussenac-Gilles, N.: Supervised Text Analysis for Ontology and Terminology Engineering. In: Proc. of the Dagstuhl Seminar 05071 on Machine Learning for the Semantic Web (2005)
Bourigault, D.: Upery: un outil d’analyse distributionnelle étendue pour la construction d’ontologies à partir de corpus. In: Actes de Traitement Automatique des Langues Naturelles, Nancy, France, pp. 75–84 (2002)
Charlet, J., Zacklad, M., Kassel, G., Bourigault, D. (eds.) Ingénierie des connaissances Evolutions récentes et nouveaux défis. Eyrolles, Paris (2000)
Cimiano, P., Pivk, A., Schmidt-Thieme, L., Staab, S.: Learning Taxonomic Relations from Heterogeneous Evidence. In: ECAI 2004 WS on Ontology Learning and Population, Valencia, Spain, pp. 59–73 (2004)
Faure, D., Poibeau, T.: First experiments of using semantic knowledge learned by ASIUM for information extraction task using INTEX. In: ECAI 2000 WS on Ontology Learning, Berlin, Germany, pp. 7–12 (2000)
Gillam, L., Tariq, M., Ahmad, K.: Terminology and the construction of ontology. Terminology 11(1), 55–81 (2005)
Girju, R., Moldovan, D.: Text Mining for Causal Relations. AAAI Conference (2002)
Hearst, M.: Automatic Acquisition of Hyponyms from Large Text Corpora. In: Proc. of the 15th Inter. Conf. on Computational Linguistics (COLING 1992), Nantes (F), pp. 539–545 (1992)
Kavanagh, J.: The Text Analyzer: a Tool for Extracting Knowledge from Text. Master’s of computer science Thesis, Univ. of Ottawa Canada (1996)
Marshman, E., Morgan, T., Meyer, I.: French patterns for expressing concept relations. Terminology 8(1), 1–30 (2002)
Rebeyrolle, J., Tanguy, L.: Repérage automatique de structures linguistiques en corpus : le cas des énoncés définitoires. Cahiers de grammaire 25, 153–174 (2000)
Reinberger, M.-L., Spyns, P.: Discovering Knowledge in Texts for the learning of DOGMA-inspired ontologies. In: ECAI 2004 WS on Ontology Learning and Population, Valencia, Spain, pp. 19–24 (2004)
Riloff, E.: Automatically Generating Extraction Patterns from Untagged Text. In: Proc. of the 13th National Conference on Artificial Intelligence (AAAI 1996), Portland, pp. 1044–1049 (1996)
Séguéla, P.: Construction de modèles de connaissances par analyse linguistique de relations lexicales dans les documents techniques. Mémoire de thèse en Informatique, Université Toulouse 3, France (2001)
Staab, S., Maedche, A.: Ontology Learning for the Semantic Web. IEEE Intelligent Systems, Special Issue on the Semantic Web 16(2), 72–79 (2001)
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Aussenac-Gilles, N., Jacques, MP. (2006). Designing and Evaluating Patterns for Ontology Enrichment from Texts. In: Staab, S., Svátek, V. (eds) Managing Knowledge in a World of Networks. EKAW 2006. Lecture Notes in Computer Science(), vol 4248. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11891451_16
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DOI: https://doi.org/10.1007/11891451_16
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