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• [P1166] Detecting Temporal Patterns of Technical Phrases by using Importance Indices in a Research Documents
  Author(s): Hidenao Abe, Shusaku Tsumoto
  
  

  Abstract
  In text mining processes, the importance indices of the technical terms play a key role in finding valuable patterns from various documents. Further, methods for finding emergent terms have attracted considerable attention as an important issue called temporal text mining. However, many conventional methods are not robust against changes in technical terms. In order to detect remarkable temporal trends of technical terms in given textual datasets robustly, we propose a method based on temporal changes in several importance indices by assuming the importance indices of the terms to be a dataset. Empirical studies show that two representative importance indices are applied to the documents from a research area. After detecting the temporal trends, we compared the emergent trend of the technical phrases to some emergent phrases given by a domain expert.

  
   

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