What is selection bias in click logs?

Selection bias in click logs is a systematic error that occurs because the data about clicks reflect not all possible options, but only those that users chose or saw. In the context of information retrieval, this means that clicks depend on the ranking of results and user behavior, not just relevance.

For example, top results in search engine results get more clicks simply because of their position, not necessarily because they are better. This distorts the data used to train ranking models, as models may learn to favor positions rather than quality.

Methods to combat selection bias include:

• Randomizing the positions of results to collect more objective clicks;
• Using models that account for click probability considering position (e.g., click models);
• Correcting data using statistical methods.

Understanding and correcting selection bias is important for creating fair and effective search and recommendation systems.