Extracting Semantic Knowledge from Wikipedia Category Names

Priya Radhakrishnan, Vasudeva Varma

Jun 26, 2013 (modified: Jun 26, 2013) AKBC 2013 submission readers: everyone
  • Decision: conferencePoster
  • Abstract: Wikipedia being a large, freely available, frequently updated and community maintained knowledge base, has been central to much recent research. However, quite often we find that the information extracted from it has extraneous content. This paper proposes a method to extract useful information from Wikipedia, using Semantic Features derived from Wikipedia categories. The proposed method provides improved performance over the state of the art Wikipedia category based method. Experimental results on benchmark datasets show that the proposed method achieves a correlation coefficient of 0.66 with human judgments. The Semantic Features derived by this method gave good correlation with human rankings in a web search query completion application.

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