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

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, 48(3), pp. 552-568. (doi: 10.1016/j.ipm.2011.07.002)

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.

• Item Type: Articles
• Keywords: Artificial intelligence, domain models, information retrieval, natural language processing
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Kim, Dr Yunhyong
• Authors: Clark, M., Kim, Y., Kruschwitz, U., Song, D., Albakour, D., Dignum, S., Beresi, U.C., Fasli, M., and De Roeck, A.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science; Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
• College/School: College of Arts & Humanities > School of Humanities > Information Studies
• Journal Name: Information Processing and Management
• ISSN: 0306-4573
• Published Online: 03 August 2011