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Documents classification by using ontology reasoning and similarity measure

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3 Author(s)
Jun Fang ; Sch. of Autom., Northwestern Polytech. Univ., Xi''an, China ; Lei Guo ; Yue Niu

Ontology-based documents classification method is introduced to solve the problem of classifier training and not considering semantic relations between words in traditional Machine Learning algorithms. However, previous work on ontology-based documents classification have some drawbacks on precision and run-time performance. In order to solve these problems, this paper proposes a novel ontology-based documents classification method by using ontology reasoning and similarity measure. Firstly, weighted terms set are extracted from documents, and categories are represented by ontologies; then the lowest concepts for each ontology is computed by using ontology reasoning techniques; next similarity score between documents and ontology is computed by using Google Distance measure; finally, web documents are assigned to categories according to the similarity score. Experimental results show our method is effective when comparing with the current ontology-based classification method, especially in the delicate classification evaluation, and the run-time performance is also better.

Published in:

Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on  (Volume:4 )

Date of Conference:

10-12 Aug. 2010