21 citations · 74 across the 9 of their papers we have counts for
12 papers
Supervised Advantage Actor-Critic for Recommender Systems
Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis +1
Casting session-based or sequential recommendation as reinforcement learning (RL) through reward signals is a promising research direction towards recommender systems (RS) that max…
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning
Dusan Stamenkovic, Alexandros Karatzoglou, Ioannis Arapakis +2
Since the inception of Recommender Systems (RS), the accuracy of the recommendations in terms of relevance has been the golden criterion for evaluating the quality of RS algorithms…
Graph Convolutional Embeddings for Recommender Systems
Paula Gómez Duran, Alexandros Karatzoglou, Jordi Vitrià +2
Modern recommender systems (RS) work by processing a number of signals that can be inferred from large sets of user-item interaction data. The main signal to analyze stems from the…
My Mouse, My Rules: Privacy Issues of Behavioral User Profiling via Mouse Tracking
Luis A. Leiva, Ioannis Arapakis, Costas Iordanou
This paper aims to stir debate about a disconcerting privacy issue on web browsing that could easily emerge because of unethical practices and uncontrolled use of technology. We de…
Impact of Response Latency on User Behaviour in Mobile Web Search
Ioannis Arapakis, Souneil Park, Martin Pielot
Traditionally, the efficiency and effectiveness of search systems have both been of great interest to the information retrieval community. However, an in-depth analysis of the inte…
Query Abandonment Prediction with Recurrent Neural Models of Mouse Cursor Movements
Lukas Brückner, Ioannis Arapakis, Luis A. Leiva
Most successful search queries do not result in a click if the user can satisfy their information needs directly on the SERP. Modeling query abandonment in the absence of click-thr…