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SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
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ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
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ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
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TSD '99 Proceedings of the Second International Workshop on Text, Speech and Dialogue
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SPIRE '99 Proceedings of the String Processing and Information Retrieval Symposium & International Workshop on Groupware
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ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
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IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
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RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
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Expert Systems with Applications: An International Journal
Automatic Topic Ontology Construction Using Semantic Relations from WordNet and Wikipedia
International Journal of Intelligent Information Technologies
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This paper proposes a method of using ontology hierarchy in automatic topic identification. The fundamental idea behind this work is to exploit an ontology hierarchical structure in order to find a topic of a text. The keywords that are extracted from a given text will be mapped onto their corresponding concepts in the ontology. By optimizing the corresponding concepts, we will pick a single node among the concepts nodes that we believe is the topic of the target text. However, a limited vocabulary problem is encountered while mapping the keywords onto their corresponding concepts. This situation forces us to extend the ontology by enriching each of its concepts with new concepts using the external linguistics knowledge-base (WordNet). Our intuition of a high number keywords mapped onto the ontology concepts is that our topic identification technique can perform at its best.