Abstract
Building domain ontology is time consuming and tedious since it is usually done by domain experts and knowledge engineers manually. This paper proposes a two-stage clustering approach for semi-automatically building ontologies from the Chinese-document corpus ba-sed on SOM neural network and agglomerative hierarchical clustering and automatically checking the ontology consistency. Chinese lexical analysis and XML Path Language(XPath) are used in the process of extracting resources from Web documents. In our experiment, this two-stage clustering approach is used for building an automobile ontology. Experimental results and the comparison with the more conventional ontology-generation method are presented and discussed, indicating the high performance of our approach. A Racer-based consistency-checking method of reasoning is presented in this paper. An ontology evolution method and performance evaluation are also given.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Noy, N.F., McGuinness, D.L.: Ontology development a guide to creating your first ontology, Technical Report KSL-01-05, Stanford Knowledge Systems Laboratory vol.101 (2001)
Astrova, I.: Reverse engineering of relational databases to ontologies. In: Bussler, C.J., Davies, J., Fensel, D., Studer, R. (eds.) ESWS 2004. LNCS, vol. 3053, pp. 327–341. Springer, Heidelberg (2004)
Zhiqing, M., Hongcan, Z., Yihua, Z., Gengui, Z.: A clustering algorithm for Chinese text based on SOM neural network and density. In: Wang, J., Liao, X.-F., Yi, Z. (eds.) ISNN 2005. LNCS, vol. 3497, pp. 251–256. Springer, Heidelberg (2005)
Bex, G.J., Maneth, S., Neven, F.: A formal model for an expressive fragment of XSLT. Information Systems 28(1), 21–39 (2002)
Bai, X., Sun, J.G., Luo, H.: WDM: A new efficient visualization method of classifying Web documents based on SOM. In: Proceedings of CIS’06, pp. 809–814. IEEE Computer Society Press, Washington (2006)
Schneider, K.M.: On word frequency information and negative evidence in Naive Bayes text classification. In: Vicedo, J.L., MartÃnez-Barco, P., MuÅ„oz, R., Saiz Noeda, M. (eds.) EsTAL 2004. LNCS (LNAI), vol. 3230, pp. 474–485. Springer, Heidelberg (2004)
Goncalves, A., Jianhan, Z., Dawei, S., Uren, V., Pacheco, R.: LRD: Latent relation discovery for vector space expansion and information retrieval. In: Yu, J.X., Kitsuregawa, M., Leong, H.V. (eds.) WAIM 2006. LNCS, vol. 4016, pp. 122–133. Springer, Heidelberg (2006)
Dasgupta, S.: Performance guarantees for hierarchical clustering. In: Kivinen, J., Sloan, R.H. (eds.) COLT 2002. LNCS (LNAI), vol. 2375, pp. 351–363. Springer, Heidelberg (2002)
Zhang, H.P., Yu, H.K., Xiong, D.Y., Liu, Q.: HHMM-based chinese lexical analyzer ICTCLAS. In: Proceedings of the 2nd SIGHAN Workshop, Sapporo, Japan, pp. 184–187 (July 2003)
Panuccio, A., Bicego, M., Murino, V.: A hidden Markov model-based approach to sequential data clustering. In: Caelli, T.M., Amin, A., Duin, R.P.W., Kamel, M.S., de Ridder, D. (eds.) SPR 2002 and SSPR 2002. LNCS, vol. 2396, pp. 734–742. Springer, Heidelberg (2002)
Ward, J.H.: Hierarchical grouping to optimize an objective function. Journoal of the American Statistical Association 58(301), 236–244 (1963)
Jena APIs, http://jena.sourceforge.net/downloads.html
Noy, N., Fergerson, R., Musen, M.: The knowledge model of Protégé-2000: Combining interoperability and flexibility. In: Dieng, R., Corby, O. (eds.) EKAW 2000. LNCS (LNAI), vol. 1937, pp. 17–32. Springer, Heidelberg (2000)
Cimiano, P., Staab, S.: Learning by googling. SIGKDD Explorations 6(2), 24–34 (2004)
Agirre, E., Ansa, O., Hovy, E., Martinez, D.: Enriching very large ontologies using the WWW. In: Proceedings of the ECAI’00 Workshop on Ontology Learning, Berlin, Germany (2000)
Zurawski, M.: Distributed multi-contextual ontology evolution–a step towards semantic autonomy. In: Staab, S., Svátek, V. (eds.) EKAW 2006. LNCS (LNAI), vol. 4248, pp. 198–213. Springer, Heidelberg (2006)
Cimiano, P., Stumme, G., Hotho, A., Tane, J.: Conceptual knowledge processing with formal concept analysis and ontologies. In: Eklund, P.W. (ed.) ICFCA 2004. LNCS (LNAI), vol. 2961, pp. 189–207. Springer, Heidelberg (2004)
Bandini, S., Calegari, S., Radaelli, P.: Towards fuzzy ontology handling vagueness of natural languages. In: Wang, G.-Y., Peters, J.F., Skowron, A., Yao, Y. (eds.) RSKT 2006. LNCS (LNAI), vol. 4062, pp. 693–700. Springer, Heidelberg (2006)
Pirrone, R., Cossentino, M., Pilato, G., Rizzo, R., Russo, G.: Discovering learning paths on a domain ontology using natural language interaction. In: Ali, M., Esposito, F. (eds.) IEA/AIE 2005. LNCS (LNAI), vol. 3533, pp. 310–314. Springer, Heidelberg (2005)
Gruber, T.R.: A translation approach to portable ontology specifications. Knowledge Acquisition 5(2), 199–220 (1993)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Bai, X., Sun, J., Li, Z., Lu, X. (2007). Domain Ontology Learning and Consistency Checking Based on TSC Approach and Racer. In: Marchiori, M., Pan, J.Z., Marie, C.d.S. (eds) Web Reasoning and Rule Systems. RR 2007. Lecture Notes in Computer Science, vol 4524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72982-2_11
Download citation
DOI: https://doi.org/10.1007/978-3-540-72982-2_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72981-5
Online ISBN: 978-3-540-72982-2
eBook Packages: Computer ScienceComputer Science (R0)