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

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• 作者：Malcolm Clark^a ; ^{mc@comp.rgu.ac.uk} ; ^{malcyc@googlemail.com} ; Yunhyong Kim^a ; Udo Kruschwitz^b ; Dawei Song^a ; Dyaa Albakour^b ; Stephen Dignum^b ; Ulises Cerviñ ; o Beresi^a ; Maria Fasli^b ; Anne De Roeck^c
• 关键词：Domain models ; Information retrieval ; Natural language processing ; Artificial intelligence
• 刊名：Information Processing and Management
• 出版年：2012
• 期刊代码：60_03064573
• 类别：cp
• 出版时间：May, 2012
• 卷：48
• 期：3
• 页码：552-568
• 文件大小：649 K

摘要

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.