Automatic Ontology-Based Knowledge Extraction From Web Documents  

Oleh:

Alani, H. ; Kim, Sanghee ; Millard, D. E. ; Weal, M. J. ; Hall, W. ; Lewis, P. H. ; Shadbolt, N. R.

Jenis: Article from Bulletin/Magazine
Dalam koleksi: IEEE Intelligent Systems vol. 18 no. 1 (2003), page 14-21.
Topik: website; automatic; ontology - based; knowledge; extraction; web documents

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II60.6 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

To bring the Semantic Web to life and provide advanced knowledge services, we need efficient ways to access and extract knowledge from Web documents. Although Web page annotations could facilitate such knowledge gathering, annotations are rare and will probably never be rich or detailed enough to cover all the knowledge these documents contain. Manual annotation is impractical and unscalable, and automatic annotation tools remain largely undeveloped. Specialized knowledge services therefore require tools that can search and extract specific knowledge directly from unstructured text on the Web, guided by an ontology that details what type of knowledge to harvest. An ontology uses concepts and relations to classify domain knowledge. Other researchers have used ontologies to support knowledge extraction, but few have explored their full potential in this domain. The paper considers the Artequakt project which links a knowledge extraction tool with an ontology to achieve continuous knowledge support and guide information extraction. The extraction tool searches online documents and extracts knowledge that matches the given classification structure. It provides this knowledge in a machine - readable format that will be automatically maintained in a knowledge base (KB). Knowledge extraction is further enhanced using a lexicon - based term expansion mechanism that provides extended ontology terminology.

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