Abstract
Ontology enrichment is required when the knowledge captured by the ontology is out of date or unable to capture the specified user requirements in a specific domain. In this paper we present an automatic statistical/semantic framework for enriching general-purpose ontologies from the World Wide Web (WWW). Using the massive amount of information encoded in texts on the web as a corpus, missing background knowledge such as concepts, instances and relations can be discovered and exploited to enrich general-purpose ontologies. The benefits of our approach are: (i) enabling ontology enrichment with missing background knowledge, and thus, enabling the reuse of such knowledge in future. (ii) saving time and effort required to manually enrich and update the ontologies. Experimental results indicate that the techniques used to enrich ontologies are both effective and efficient.
This is a preview of subscription content, log in via an institution to check access.
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
Miller, G.A.: WordNet: A Lexical Database for English. Communications of the ACM 38(1), 39–41 (1995)
Lenat, D.B.: Cyc: a large-scale investment in knowledge infrastructure. Communications of the ACM 38(11), 33–38 (1995)
Hearst, M.A.: Automatic acquisition of hyponyms from large text corpora. In: Proceeding of COLING 1992, Nantes, France, pp. 539–545 (1992)
Eneko Agirre, E.H., Ansa, O., Martinez, D.: Enriching Very Large Ontologies Using the WWW. In: Proc. ECAI Workshop on Ontology Learning (2000)
Maedche, A., Staab, S.: Ontology Learning for the Semantic Web. IEEE Intelligent Systems 16(2), 72–79 (2001)
Faure, F., Poibeau, T.: First Experiments of using semantic knowledge learned by ASIUM for information extraction task using INTEX. In: Proceedings of ECAI Workshop on ontology Learning, pp. 7–12 (2000)
Clerkin, P., Cunningham, P., Hayes, C.: Ontology Discovery for the Semantic Web Using Hierarchical Clustering. In: Proc. of (ECML/PKDD 2001), pp. 1–12 (2001)
Maedche, V., Pekar, A., Staab, S.: Ontology Learning Part One- On Discovering Taxonomic Relations from the Web, pp. 301–322. Springer, Heidelberg (2002)
Xu, F., Kurz, D., Piskorski, J., Schmeier, S.: A Domain Adaptive Approach to Automatic Acquisition of Domain Relevant Terms and Their Relations with Bootstrapping. In: Proc. Third Int’l Conf. Language Resources and Evaluation, LREC 2002 (2002)
Faatz, A., Steinmetz, R.: Ontology Enrichment with Texts from the WWW. In: Semantic Web Mining, WS 2002 (2002)
Khan, L., Luo, F.: Ontology Construction for Information Selection. In: Proc. of 14th IEEE Int’l Conf. Tools with Artificial Intelligence,, pp. 122–127 (2002)
Navigli, R., Velardi, P., Gangemi, A.: Ontology Learning and Its Applications to Automatied Terminilogy Translation. IEEE Intelligent Systems 18(1), 22–31 (2003)
Cimiano, P., Hatho, A., Staab, S.: Learning concept hierarchies from text corpora using fomal concept analysis. JAIR 24, 305–339 (2005)
Cilibrasi, R., Vitanyi, P.: The Google Similarity Distance. IEEE Transactions on Knowledge and Data Engineering 19(3), 370–383 (2007)
Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V.: GATE: a framework and graphical development environment for robust NLP tools and applications. In: Proc. of the 40th Anniversary Meeting of the Associ ation for Computational Linguistics, Phil., USA (2002)
Giunchiglia, F., et al.: S-Match: an Algorithm and an Implementation of Semantic Matching. In: Proc. of ESW, pp. 61–75 (2004)
Trojahn, C., et al.: A Cooperative Approach for Composite Ontology Mapping. In: Spaccapietra, S. (ed.) Journal on Data Semantics X. LNCS, vol. 4900, pp. 237–263. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Maree, M., Belkhatir, M., Alhashmi, S.M. (2011). General-Purpose Ontology Enrichment from the WWW. In: Wang, H., Li, S., Oyama, S., Hu, X., Qian, T. (eds) Web-Age Information Management. WAIM 2011. Lecture Notes in Computer Science, vol 6897. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23535-1_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-23535-1_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23534-4
Online ISBN: 978-3-642-23535-1
eBook Packages: Computer ScienceComputer Science (R0)