65 citations · 81 across the 3 of their papers we have counts for
6 papers
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…
Rethinking Supervised Learning and Reinforcement Learning in Task-Oriented Dialogue Systems
Ziming Li, Julia Kiseleva, Maarten de Rijke
Dialogue policy learning for task-oriented dialogue systems has enjoyed great progress recently mostly through employing reinforcement learning methods. However, these approaches h…
Accelerated Convergence for Counterfactual Learning to Rank
Rolf Jagerman, Maarten de Rijke
Counterfactual Learning to Rank (LTR) algorithms learn a ranking model from logged user interactions, often collected using a production system. Employing such an offline learning…
HiTR: Hierarchical Topic Model Re-estimation for Measuring Topical Diversity of Documents
Hosein Azarbonyad, Mostafa Dehghani, Tom Kenter +3
A high degree of topical diversity is often considered to be an important characteristic of interesting text documents. A recent proposal for measuring topical diversity identifies…
Explainable Outfit Recommendation with Joint Outfit Matching and Comment Generation
Yujie Lin, Pengjie Ren, Zhumin Chen +3
Most previous work on outfit recommendation focuses on designing visual features to enhance recommendations. Existing work neglects user comments of fashion items, which have been…
DATA:SEARCH'18 -- Searching Data on the Web
Paul Groth, Laura Koesten, Philipp Mayr +2
This half day workshop explores challenges in data search, with a particular focus on data on the web. We want to stimulate an interdisciplinary discussion around how to improve th…