Content clouds: Classifying content in Web 2.0

  • Cosh K
  • Burns R
  • Daniel T
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Abstract

With increasing amounts of user generated content being produced electronically in the form of wikis, blogs, forums etc. the purpose of this paper is to investigate a new approach to classifying ad hoc content. Design/methodology/approach – The approach applies natural language processing (NLP) tools to automatically extract the content of some text, visualizing the results in a content cloud. Findings – Content clouds share the visual simplicity of a tag cloud, but display the details of an article at a different level of abstraction, providing a complimentary classification. Research limitations/implications – Provides the general approach to creating a content cloud. In the future, the process can be refined and enhanced by further evaluation of results. Further work is also required to better identify closely related articles. Practical implications – Being able to automatically classify the content generated by web users will enable others to find more appropriate content. Originality/value – The approach is original. Other researchers have produced a cloud, simply by using skiplists to filter unwanted words, this paper’s approach improves this by applying appropriate NLP

Author-supplied keywords

  • Classification
  • Content management
  • Internet
  • Tagging

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Authors

  • Kenneth J. Cosh

  • Robert Burns

  • Toby Daniel

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