Cerno: Light-weight tool support for semantic annotation of textual documents

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• 作者：Nadzeya Kiyavitskaya ; Nicola Zeni ; James R. Cordy ; Luisa Mich ; John Mylopoulos
• 关键词：8.4 Semantic web ; 23 Natural language for DKE ; 20.1 Re- and reverse engineering ; Semantic annotation
• 刊名：Data and Knowledge Engineering
• 出版年：2009
• 出版时间：December 2009
• 年：2009
• 卷：68
• 期：12
• 页码：1470-1492
• 全文大小：1948 K

文摘

Enrichment of text documents with semantic metadata reflecting their meaning facilitates document organization, indexing and retrieval. However, most web data remain unstructured because of the difficulty and the cost of manually annotating text. In this work, we present Cerno, a framework for semi-automatic semantic annotation of textual documents according to a domain-specific semantic model. The proposed framework is founded on light-weight techniques and tools intended for legacy code analysis and markup. To illustrate the feasibility of our proposal, we report experimental results of its application to two different domains. These results suggest that light-weight semi-automatic techniques for semantic annotation are feasible, require limited human effort for adaptation to a new domain, and demonstrate markup quality comparable with state-of-the-art methods.