Categorisation of web documents using extraction ontologies. (12th November 2008)

• Record Type: Journal Article
• Authors: Xu, Li; Embley, David W.
• Is Part Of: International journal of metadata, semantics and ontologies. Volume 3:Number 1(2008)
• Page Start: 3
• Page End: 20
• Publication Date: 2008-11-12
• Subjects: document categorisation -- web documents -- document classification -- extraction ontologies -- HTML documents -- information extraction -- machine learning -- internet -- information retrieval; Metadata -- Periodicals; Semantic Web -- Periodicals; Ontologies (Information retrieval) -- Periodicals; Data structures (Computer science) -- Periodicals; Information theory -- Periodicals; 005.74
• Languages: English
• ISSNs: 1744-2621

Abstract

Automatically recognising which HTML documents on the Web contain items of interest for a user is non-trivial. As a step toward solving this problem, we propose an approach based on information-extraction ontologies. Given HTML documents, tables, and forms, our document recognition system extracts expected ontological vocabulary (keywords and keyword phrases) and expected ontological instance data (particular values for ontological concepts). We then use machine-learned rules over this extracted information to determine whether an HTML document contains items of interest. Experimental results show that our ontological approach to categorisation works well, having achieved F-measures above 90% for all applications we tried.