An automatic approach to classify web documents using a domain ontology

  • Authors:

  • Mu-Hee Song;Soo-Yeon Lim;Seong-Bae Park;Dong-Jin Kang;Sang-Jo Lee

  • Affiliations:

  • Dept. of Computer Engineering, Information Technology Services, Kyungpook National University, Daegu, The Korea;Dept. of Computer Engineering, Information Technology Services, Kyungpook National University, Daegu, The Korea;Dept. of Computer Engineering, Information Technology Services, Kyungpook National University, Daegu, The Korea;Dept. of Computer Engineering, Information Technology Services, Kyungpook National University, Daegu, The Korea;Dept. of Computer Engineering, Information Technology Services, Kyungpook National University, Daegu, The Korea

  • Venue:
  • PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
  • Year:
  • 2005

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Abstract

This paper suggests an automated method for document classification using an ontology, which expresses terminology information and vocabulary contained in Web documents by way of a hierarchical structure. Ontologybased document classification involves determining document features that represent the Web documents most accurately, and classifying them into the most appropriate categories after analyzing their contents by using at least two pre-defined categories per given document features. In this paper, Web documents are classified in real time not with experimental data or a learning process, but by similar calculations between the terminology information extracted from Web texts and ontology categories. This results in a more accurate document classification since the meanings and relationships unique to each document are determined.