Automatically structuring domain knowledge from text: an overview of current research.

Clark, Malcolm; Kim, Yunhyong; Kruschwitz, Udo; Song, Dawei; Albakour, Dyaa; Dignum, Stephen; Beresi, Ulises Cervi�o; Fasli, Maria; De Roeck, Anne

Abstract

This paper presents an overview of automatic methods for building domain knowledge structures (domain models) from text collections. Applications of domain models have a long history within knowledge engineering and artificial intelligence. In the last couple of decades they have surfaced noticeably as a useful tool within natural language processing, information retrieval and semantic web technology. Inspired by the ubiquitous propagation of domain model structures that are emerging in several research disciplines, we give an overview of the current research landscape and some techniques and approaches. We will also discuss trade-offs between different approaches and point to some recent trends.

Citation

CLARK, M., KIM, Y., KRUSCHWITZ, U., SONG, D., ALBAKOUR, D., DIGNUM, S., BERESI, U. C., FASLI, M. and DE ROECK, A. 2012. Automatically structuring domain knowledge from text: an overview of current research. Information processing and management [online], 48(3), pages 552-568. Available from: https://doi.org/10.1016/j.ipm.2011.07.002

• Journal Article Type: Article
• Acceptance Date: Jul 6, 2011
• Online Publication Date: Aug 3, 2011
• Publication Date: May 31, 2012
• Deposit Date: Mar 13, 2015
• Publicly Available Date: Mar 13, 2015
• Journal: Information processing and management
• Print ISSN: 0306-4573
• Electronic ISSN: 1873-5371
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 48
• Issue: 3
• Pages: 552-568
• DOI: https://doi.org/10.1016/j.ipm.2011.07.002
• Keywords: Domain models; Information retrieval; Natural language processing; Artificial intelligence
• Public URL: http://hdl.handle.net/10059/1165