Abstract
Semantic Web provides a knowledge-based environment that enables information to be shared and retrieved effectively. In this research, we propose the Scholarly Semantic Web for the sharing, reuse and management of scholarly information. To support the Scholarly Semantic Web, we need to construct ontology from data which is a tedious and difficult task. To generate ontology automatically, Formal Concept Analysis (FCA) is an effective technique that can formally abstract data as conceptual structures. To enable FCA to deal with uncertainty in data and interpret the concept hierarchy reasonably, we propose to incorporate fuzzy logic into FCA for automatic generation of ontology. The proposed new framework is known as Fuzzy Formal Concept Analysis (FFCA). In this paper, we will discuss the Scholarly Semantic Web, and the ontology generation process from the FFCA framework. In addition, the performance of the FFCA framework for ontology generation will also be evaluated and presented.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web, Scientific American (2001), Available at: http://www.sciam.com/2001/0501issue/0501bernerslee.html
Guarino, N., Giaretta, P.: Ontologies and Knowledge Bases: Towards a Terminological Clarification. In: Toward Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing, IOS Press, Amsterdam (1995)
Noy, N., McGuinness, D.L.: Ontology Development 101: A Guide to Creating Your First Ontology. Report SMI-2001-0880, Department of Mechanical and Industrial Engineering, University of Toronto (2001)
Bechhofer, S., Horrocks, I., Patel-Schneider, P., Tessaris, S.: A Proposal for a Description Logic Interface. In: Proceedings of the International Workshop on Description Logics, pp. 33–36 (1999)
Maedche, A., Staab, S.: Mining Ontologies from Text. In: Dieng, R., Corby, O. (eds.) EKAW 2000. LNCS (LNAI), vol. 1937, pp. 189–202. Springer, Heidelberg (2000)
Doan, A., Madhavan, J., Domingos, P., Halevy, A.Y.: Learning to Map Between Ontologies on the Semantic Web. In: Proceedings of the Eleventh International World Wide Web Conference, WWW 2002, Honolulu, Hawaii, USA, pp. 662–673 (2002)
Jain, A.K., Dubes, R.C.: Algorithms for Clustering Data. Prentice-Hall, Englewood Cliffs (1988)
Ganter, B., Wille, R.: Formal Concept Analysis. Springer, Heidelberg (1999)
Hotho, A., Staab, S., Stumme, G.: Explaining Text Clustering Results using Semantic Structures. In: Lavrač, N., Gamberger, D., Todorovski, L., Blockeel, H. (eds.) PKDD 2003. LNCS (LNAI), vol. 2838, pp. 217–228. Springer, Heidelberg (2003)
Zadeh, L.A.: Fuzzy Logic and Approximate Reasoning. Synthese 30, 407–428 (1975)
Wiederhold, G.: Digital Libraries, Value, and Productivity. Communications of the ACM 38(4), 85–96 (1995)
ISI, Institute for Scientific Information (2000), Available at: http://www.isinet.com
Bollacker, K., Lawrence, S., Giles, C.: Discovering Relevant Scientific Literature on the Web. IEEE Intelligent Systems 15(2), 42–47 (2000)
Kampa, S., Miles-Board, T., Carr, L.: Hypertext in the Semantic Web. In: Proceedings ACM Conference on Hypertext and Hypermedia, Aarhus, Denmark, pp. 237–238 (2001)
Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning. Part I: Inf. Science 8, 199–249; Part II: Inf. Science 8, 301–357; Part III: Inf. Science 9, 43-80 (1975)
Zadeh, L.A.: Fuzzy Sets. Journal of Information and Control 8, 338–353 (1965)
DARPA, DAML-ONT Initial Release (2000), Available at: http://www.daml.org/2000/10/daml-ont.html
Chu, W., Chiang, K.: Abstraction of High Level Concepts from Numerical Values in Databases. In: Proceedings of AAAI Workshop on Knowledge Discovery in Databases, pp. 133–144 (1994)
Nanas, N., Uren, V., de Roeck, A.: Building and Applying a Concept Hierarchy Representation of a User Profile. In: Proceedings of the 26th annual international ACM SIGIR Conference on Research and Development in Information Retrieval, ACM Press, New York (2003)
Chu, W., Chen, Q.: Neighborhood and associative query answering. Journal of Intelligent Information Systems 1(3) (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Quan, T.T., Hui, S.C., Fong, A.C.M., Cao, T.H. (2004). Automatic Generation of Ontology for Scholarly Semantic Web. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds) The Semantic Web – ISWC 2004. ISWC 2004. Lecture Notes in Computer Science, vol 3298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30475-3_50
Download citation
DOI: https://doi.org/10.1007/978-3-540-30475-3_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23798-3
Online ISBN: 978-3-540-30475-3
eBook Packages: Springer Book Archive