Click model
A click model is a predictive model of the likelihood that a user clicks a particular result, advertisement, or other presented item.
AI-Powered Search
A click model is a model that represents or predicts user clicks on search results to infer their relevance or examination behavior.
- How it is used
- Turns search clicks into implicit relevance judgments for automated LTR retraining.
- How deep it goes
- Works through session-based CTR calculation, then identifies position and confidence biases rather than detailing the full LTR retraining process.
- Examples
- Uses ranked movie-query sessions, pandas CTR calculations, pairwise relevance grades, and a failed A/B test.
- What you can do after
- Build it from scratch as session-based CTR judgments, then diagnose bias before feeding judgments into LTR.
Experimentation for Engineers
A click model is a predictive model that estimates the likelihood that a user will click a particular advertisement.
- How it is used
- Uses predicted click probabilities to select advertisements and optimize production CTR and revenue.
- How deep it goes
- Explains serving flow, binary click measurement, A/B evaluation, and epsilon-greedy experimentation, but not model-training internals.
- Examples
- Uses simulated models with CTRs 0.005 and 0.007, a 91,561-measurement A/B test, and four epsilon-greedy arms.
- What you can do after
- Evaluate click models in production and configure experiments that balance CTR gains against exploratory exposure.
Read how Experimentation for Engineers explains click model →
Related concepts
- probabilistic judgmentproduces · A probabilistic judgment is a relevance assessment represented as a probability that a user considers a result relevant.
- human-in-the-loopproduces · Human-in-the-loop is a system pattern in which people provide input, judgment, review, or intervention within an automated process.
- judgment listproduces · A judgment list is a collection of labeled query-document pairs containing human or system relevance judgments.
- click-through rateuses · Click-through rate is the proportion of displayed or offered items that receive a click.
- simplified dynamic Bayesian networkincludes · A simplified dynamic Bayesian network is a probabilistic click model that estimates search-result relevance from user examination and click behavior.
- implicit feedbackproduces · Implicit feedback is indirect evidence about user preferences or judgments inferred from observed behavior rather than explicitly stated ratings or evaluations.
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