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Learning User Clicks in Web Search

Learning User Clicks in Web Search. Ding Zhou et al . The Pennsylvania State University IJCAI 2007. What is Click Prediction?. microsoft xbox 360 kinect game http://www.xbox.com/zh-TW/kinect http://www.xbox.com/en-US/kinect http://en.wikipedia.org/wiki/Kinect. What is Click Prediction?.

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Learning User Clicks in Web Search

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  1. Learning User Clicks in Web Search Ding Zhou et al. The Pennsylvania State University IJCAI 2007

  2. What is Click Prediction? • microsoft xbox 360 kinect game • http://www.xbox.com/zh-TW/kinect • http://www.xbox.com/en-US/kinect • http://en.wikipedia.org/wiki/Kinect

  3. What is Click Prediction? • microsoft xbox 360 kinect game • http://www.xbox.com/zh-TW/kinect • http://www.xbox.com/en-US/kinect •  http://en.wikipedia.org/wiki/Kinect

  4. Click Prediction Model • P(http://www.xbox.com/zh-TW/kinect | microsoft xbox 360 kinect game) • P(http://www.xbox.com/en-US/kinect | microsoft xbox 360 kinect game) • P(http://en.wikipedia.org/wiki/Kinect | microsoft xbox 360 kinect game)

  5. Two approaches • Full Model: PF(http://www.xbox.com/zh-TW/kinect | “microsoft xbox 360 kinect game”) • Independent Model: PI(http://www.xbox.com/zh-TW/kinect | microsoft, xbox, 360, kinect, game)

  6. Two Approaches: Pros and Cons • Full Model • High prediction accuracy • Low coverage • Independent Model • Low prediction accuracy • High coverage

  7. New Approach: Conditional Probability Hierarchy • P(url | microsoft xbox 360 kinect game) = PF(url | “microsoft xbox 360 kinect game”) + (1-)PI(url | microsoft, xbox, 360, kinect, game)

  8. New Approach: Conditional Probability Hierarchy • P(url | microsoft xbox 360 kinect game) = PF(url | “microsoft xbox 360 kinect game”) + (1-)PI(url | microsoft, xbox, 360, kinect, game) • PI(url | microsoft, xbox, 360, kinect, game) = P(url|microsoft)P(url|xbox)P(url|360)P(url|kinect) P(url|game)

  9. New Approach: Conditional Probability Hierarchy • P(url | microsoft xbox 360 kinect game) = PF(url | “microsoft xbox 360 kinect game”) + (1-)PI(url | microsoft, xbox, 360, kinect, game) • PI(url | microsoft, xbox, 360, kinect, game) = P(url|microsoft)P(url|xbox)P(url|360)P(url|kinect) P(url|game)

  10. New Approach: Conditional Probability Hierarchy P(url|microsoft xbox 360 kinect game) P(url|360 kinect game) P(url|microsoft xbox) P(url|360 kinect) game xbox 360 kinect microsoft

  11. New Approach: Conditional Probability Hierarchy • P(url | microsoft xbox 360 kinect game) = PF(url | “microsoft xbox 360 kinect game”) + (1-)PI(url | microsoft, xbox, 360, kinect, game) • PI(url | microsoft, xbox, 360, kinect, game) = f(PF(url | “microsoft xbox”), (1-)PI(url | microsoft, xbox), PF(url | “360 kinect game”), (1-)PI(url | 360, kinect, game))

  12. New Approach: Conditional Probability Hierarchy • P(url | microsoft xbox 360 kinect game) = PF(url | “microsoft xbox 360 kinect game”) + (1-)PI(url | microsoft, xbox, 360, kinect, game) •  is directly proportional to the occurrence frequency of “microsoft xbox 360 kinect game”

  13. How to predict? • What’s the threshold probability for considering P(url | microsoft xbox 360 kinect game) as a click???

  14. How to predict? • What’s the threshold probability for considering P(url | microsoft xbox 360 kinect game) as a click??? • Not said in paper…

  15. Experimental Corpus • CiteSeer • 1,826,817 query-click pairs

  16. Prediction Accuracy

  17. Prediction Coverage

  18. Accuracy-Coverage Tradeoff

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