Generic title labeling for clustered documents

Yuen Hsien Tseng*


研究成果: 雜誌貢獻期刊論文同行評審

29 引文 斯高帕斯(Scopus)


Document clustering is a powerful technique to detect topics and their relations for information browsing, analysis, and organization. However, clustered documents require post-assignment of descriptive titles to help users interpret the results. Existing techniques often assign labels to clusters based only on the terms that the clustered documents contain, which may not be sufficient for some applications. To solve this problem, 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.

頁(從 - 到)2247-2254
期刊Expert Systems with Applications
出版狀態已發佈 - 2010 3月 15

ASJC Scopus subject areas

  • 工程 (全部)
  • 電腦科學應用
  • 人工智慧


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