iScore: Measuring the Interestingness of Articles in a Limited User Environment

@article{Pon2007iScoreMT,
  title={iScore: Measuring the Interestingness of Articles in a Limited User Environment},
  author={Raymond K. Pon and Alfonso F. Cardenas and David J. Buttler and Terence Critchlow},
  journal={2007 IEEE Symposium on Computational Intelligence and Data Mining},
  year={2007},
  pages={354-361}
}
  • Raymond K. Pon, Alfonso F. Cardenas, +1 author Terence Critchlow
  • Published in
    IEEE Symposium on…
    2007
  • Computer Science
  • Search engines, such as Google, assign scores to news articles based on their relevancy to a query. However, not all relevant articles for the query may be interesting to a user. For example, if the article is old or yields little new information, the article would be uninteresting. Relevancy scores do not take into account what makes an article interesting, which would vary from user to user. Although methods such as collaborative filtering have been shown to be effective in recommendation… CONTINUE READING

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