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YANG Zhen, DUAN Li-juan, LAI Ying-xu. Online Public Opinion Hotspot Detection and Analysis Based on Short Text Clustering Using String Distance[J]. Journal of Beijing University of Technology, 2010, 36(5): 669-673.
Citation: YANG Zhen, DUAN Li-juan, LAI Ying-xu. Online Public Opinion Hotspot Detection and Analysis Based on Short Text Clustering Using String Distance[J]. Journal of Beijing University of Technology, 2010, 36(5): 669-673.
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Online Public Opinion Hotspot Detection and Analysis Based on Short Text Clustering Using String Distance

  • College of Computer Science, Beijing University of Technology, Beijing 100124, China

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  • Received Date: December 09, 2009
  • Available Online: December 14, 2022
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    • Abstract
  • The unique language characteristic of short texts has made the performance of traditional natural language processing methods degradation,or even unavailable.Exact representation and calculation of the similarity between short texts are great helpful to content based clustering.That this paper treated each short text as a composition of characters,numbers and punctuation,and a similarity measure based on string similarity was proposed.Then a public opinion hotspot detection and analysis system based on short text hierarchical clustering was built.This method calculated the similarity directly which skipped the feature extraction and representation processing of short text,to a certain extent,and avoided using the sparse feature vectors.Experimental results show the effectiveness of the proposed method.
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    • References (8)
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