Evaluating the Robustness of Learning from Implicit Feedback

Filip Radlinski; Thorsten Joachims

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Evaluating the Robustness of Learning from Implicit Feedback

Filip Radlinski·Thorsten Joachims

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Abstract

This paper evaluates the robustness of learning from implicit feedback in web search. In particular, we create a model of user behavior by drawing upon user studies in laboratory and real-world settings. The model is used to understand the effect of user behavior on the performance of a learning algorithm for ranked retrieval. We explore a wide range of possible user behaviors and find that learning from implicit feedback can be surprisingly robust. This complements previous results that demonstrated our algorithm's effectiveness in a real-world search engine application.

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Filip Radlinski, Thorsten Joachims. 2006-05-08. Evaluating the Robustness of Learning from Implicit Feedback. https://arxiv.org/abs/cs/0605036

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