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Domain ontology graph model and its application in Chinese text classification

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Abstract

This paper proposes an ontology learning method which is used to generate a graphical ontology structure called ontology graph. The ontology graph defines the ontology and knowledge conceptualization model, and the ontology learning process defines the method of semiautomatic learning and generates ontology graphs from Chinese texts of different domains, the so-called domain ontology graph (DOG). Meanwhile, we also define two other ontological operations—document ontology graph generation and ontology graph-based text classification, which can be carried out with the generated DOG. This research focuses on Chinese text data, and furthermore, we conduct two experiments: the DOG generation and ontology graph-based text classification, with Chinese texts as the experimental data. The first experiment generates ten DOGs as the ontology graph instances to represent ten different domains of knowledge. The generated DOGs are then further used for the second experiment to provide performance evaluation. The ontology graph-based approach is able to achieve high text classification accuracy (with 92.3 % in f-measure) over other text classification approaches (such as 86.8 % in f-measure for tf–idf approach). The better performance in the comparative experiments reveals that the proposed ontology graph knowledge model, the ontology learning and generation process, and the ontological operations are feasible and effective.

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Acknowledgments

The authors are very grateful for the editors and anonymous reviewers. Their many valuable and constructive comments and suggestions helped us significantly improve this work. This work was supported in part by the GRF Grant 5237/08E, by the CRG Grant G-U756 of The Hong Kong Polytechnic University, and by the National Natural Science Foundations of China under Grant 60903088 and Grant 61170040.

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Authors and Affiliations

  1. Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    James N. K. Liu & Edward H. Y. Lim

  2. College of Mathematics and Computer Science, Hebei University, Baoding, 071002, China

    Yu-lin He & Xi-zhao Wang

Authors
  1. James N. K. Liu
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  2. Yu-lin He
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  3. Edward H. Y. Lim
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  4. Xi-zhao Wang
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Correspondence to James N. K. Liu or Yu-lin He.

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Liu, J.N.K., He, Yl., Lim, E.H.Y. et al. Domain ontology graph model and its application in Chinese text classification. Neural Comput & Applic 24, 779–798 (2014). https://doi.org/10.1007/s00521-012-1272-z

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  • DOI: https://doi.org/10.1007/s00521-012-1272-z

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