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Spam user detection report

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Pixnet Hackathon 2015

Published in: Technology
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Spam user detection report

  1. 1. Spam User Detection Andy, Len, Petertc
  2. 2. Agenda  Machine Learning Tools  AWS Machine Learning  Azure Machine Learning  Spam Detection Algorithm  Detect spam user by time frequency.  Detect spam user by article correlation.
  3. 3. Machine Learning Tools
  4. 4. AWS Machine Learning
  5. 5. AWS Machine Learning
  6. 6. Azure Machine Learning  https://manage.windowsazure.com
  7. 7. Spam Detection Algorithm
  8. 8. Detect spam user by time frequency.
  9. 9. Detect spam user by time frequency. 500,000 actions
  10. 10. Detect spam user by time frequency. 1,000,000 actions 500,000 actions
  11. 11. Detect spam user by time frequency. 1,000,000 actions 3,000,000 actions
  12. 12. Detect spam user by article correlation. Spam User Spam User Spam User High correlation High correlation High correlation
  13. 13. Detect spam user by article correlation. Title_count Article_count High correlation
  14. 14. Thanks!

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