A cluster labeling algorithm for creating generic titles based on external resources such as WordNet is proposed. Our method first extracts category-specific terms as cluster descriptors. These descriptors are then mapped to generic terms based on a hypernym search algorithm. The proposed method has been evaluated on a patent document collection and a subset of the Reuters-21578 collection. Experimental results revealed that our method performs as anticipated. Real-case applications of these generic terms show promising in assisting humans in interpreting the clustered topics. Our method is general enough such that it can be easily extended to use other hierarchical resources for adaptable label generation. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Tseng, Y. H., Lin, C. J., Chen, H. H., & Lin, Y. I. (2006). Toward generic title generation for clustered documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4182 LNCS, pp. 145–157). Springer Verlag. https://doi.org/10.1007/11880592_12
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