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Automatic building of an ontology on the basis of text corpora in Thai

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Abstract

This paper presents a methodology for automatic learning of ontologies from Thai text corpora, by extraction of terms and relations. A shallow parser is used to chunk texts on which we identify taxonomic relations with the help of cues: lexico-syntactic patterns and item lists. The main advantage of the approach is that it simplify the task of concept and relation labeling since cues help for identifying the ontological concept and hinting their relation. However, these techniques pose certain problems, i.e. cue word ambiguity, item list identification, and numerous candidate terms. We also propose the methodology to solve these problems by using lexicon and co-occurrence features and weighting them with information gain. The precision, recall and F-measure of the system are 0.74, 0.78 and 0.76, respectively.

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Notes

  1. http://www.fao.org/agrovoc/

  2. Thai National Agricultural Information Coordinating Center (http://www.thaiagris.lib.ku.ac.th/).

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Acknowledgments

The authors would like to present deeply thanks to Michael Zock and Mathieu Lafourcade for their patience to review this work. The work described in this paper has been supported by the grant of NECTEC No. NT-B-22-14-12-46-06. It was also funded in part by the KURDI; Kasetsart University Research and Development Institute.

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  1. NAiST Laboratory, Kasetsart University, Bangkok, Thailand

    Aurawan Imsombut & Asanee Kawtrakul

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  1. Aurawan Imsombut
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  2. Asanee Kawtrakul
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Correspondence to Aurawan Imsombut.

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Imsombut, A., Kawtrakul, A. Automatic building of an ontology on the basis of text corpora in Thai. Lang Resources & Evaluation 42, 137–149 (2008). https://doi.org/10.1007/s10579-007-9045-5

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