%0 Conference Paper %1 Hierarchy01automatictopic %A Hierarchy, Using Ontology %A Tiun, Sabrina %A Abdullah, Rosni %A Kong, Tang Enya %B In the Proc. of the 2 nd International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2001 %D 2001 %K identification text topic %P 444--453 %T Automatic Topic Identification %U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.1560 %X 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 which 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 which 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.

@inproceedings{Hierarchy01automatictopic, abstract = {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 which 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 which 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.}, added-at = {2009-09-09T05:47:29.000+0200}, author = {Hierarchy, Using Ontology and Tiun, Sabrina and Abdullah, Rosni and Kong, Tang Enya}, biburl = {https://www.bibsonomy.org/bibtex/2cc8b1bb3683125efdbcf8050ad40a3e3/huiyangsfsu}, booktitle = {In the Proc. of the 2 nd International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2001}, description = {Automatic Topic Identification ontology based}, interhash = {443fb137050429329beafa8ff0db08ba}, intrahash = {cc8b1bb3683125efdbcf8050ad40a3e3}, keywords = {identification text topic}, pages = {444--453}, timestamp = {2009-09-09T05:47:29.000+0200}, title = {Automatic Topic Identification}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.1560}, year = 2001 }