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9 papers · 1 filter
Unifying Online and Counterfactual Learning to Rank
Harrie Oosterhuis, Maarten de Rijke
Optimizing ranking systems based on user interactions is a well-studied problem. State-of-the-art methods for optimizing ranking systems based on user interactions are divided into…
When Inverse Propensity Scoring does not Work: Affine Corrections for Unbiased Learning to Rank
Ali Vardasbi, Harrie Oosterhuis, Maarten de Rijke
Besides position bias, which has been well-studied, trust bias is another type of bias prevalent in user interactions with rankings: users are more likely to click incorrectly w.r.…
Taking the Counterfactual Online: Efficient and Unbiased Online Evaluation for Ranking
Harrie Oosterhuis, Maarten de Rijke
Counterfactual evaluation can estimate Click-Through-Rate (CTR) differences between ranking systems based on historical interaction data, while mitigating the effect of position bi…
An Analysis of Mixed Initiative and Collaboration in Information-Seeking Dialogues
Svitlana Vakulenko, Evangelos Kanoulas, Maarten de Rijke
The ability to engage in mixed-initiative interaction is one of the core requirements for a conversational search system. How to achieve this is poorly understood. We propose a set…
Cascade Model-based Propensity Estimation for Counterfactual Learning to Rank
Ali Vardasbi, Maarten de Rijke, Ilya Markov
Unbiased CLTR requires click propensities to compensate for the difference between user clicks and true relevance of search results via IPS. Current propensity estimation methods a…
Query Resolution for Conversational Search with Limited Supervision
Nikos Voskarides, Dan Li, Pengjie Ren +2
In this work we focus on multi-turn passage retrieval as a crucial component of conversational search. One of the key challenges in multi-turn passage retrieval comes from the fact…