1

Learning User Clicks in Web Search

Ding Zhou et al.The Pennsylvania State

UniversityIJCAI 2007

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What is Click Prediction?

microsoft xbox 360 kinect game1. http://www.xbox.com/zh-TW/kinect2. http://www.xbox.com/en-US/kinect3. http://en.wikipedia.org/wiki/Kinect

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What is Click Prediction?

microsoft xbox 360 kinect game11 http://www.xbox.com/zh-TW/kinect11 http://www.xbox.com/en-US/kinect11 http://en.wikipedia.org/wiki/Kinect

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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)

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Two approaches

1. Full Model: PF(http://www.xbox.com/zh-TW/kinect | “microsoft xbox 360 kinect game”)

2. Independent Model: PI(http://www.xbox.com/zh-TW/kinect | microsoft, xbox, 360, kinect, game)

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Two Approaches: Pros and Cons

Full Model High prediction accuracy Low coverage

Independent Model Low prediction accuracy High coverage

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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)

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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)

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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)

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New Approach: Conditional Probability Hierarchy

microsoft xbox 360 kinect game

P(url|microsoft xbox)P(url|360 kinect)

P(url|360 kinect game)

P(url|microsoft xbox 360 kinect game)

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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))

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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”

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How to predict? What’s the threshold probability for considering

P(url | microsoft xbox 360 kinect game) as a click???

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How to predict? What’s the threshold probability for considering

P(url | microsoft xbox 360 kinect game) as a click??? Not said in paper…

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Experimental Corpus

CiteSeer 1,826,817 query-click pairs

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Prediction Accuracy

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Prediction Coverage

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Accuracy-Coverage Tradeoff