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      • 2013 Working Papers
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      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 2013 Working Papers
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      Text categorization and similarity analysis: similarity measure, literature review

      Fowke, Michael; Hinze, Annika; Heese, Ralf
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      Fowke, M., Hinze, A., & Heese, R.(2013). Text categorization and similarity analysis: similarity measure, literature review. (Working paper 11/2013). Hamilton, New Zealand: University of Waikato, Department of Computer Science.
      Permanent Research Commons link: https://hdl.handle.net/10289/8432
      Abstract
      Document classification and provenance has become an important area of computer science as the amount of digital information is growing significantly. Organisations are storing documents on computers rather than in paper form. Software is now required that will show the similarities between documents (i.e. document classification) and to point out duplicates and possibly the history of each document (i.e. provenance). Poor organisation is common and leads to situations like above. There exists a number of software solutions in this area designed to make document organisation as simple as possible. I'm doing my project with Pingar who are a company based in Auckland who aim to help organise the growing amount of unstructured digital data. This reports analyses the existing literature in this area with the aim to determine what already exists and how my project will be different from existing solutions.
      Date
      2013-12
      Type
      Working Paper
      Series
      Computer Science Working Papers
      Report No.
      11/2013
      Publisher
      University of Waikato, Department of Computer Science
      Rights
      © 2013 Michael Fowke, Annika Hinze, Ralf Heese.
      Collections
      • 2013 Working Papers [13]
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