Dimitris Paraschakis

According to our database, Dimitris Paraschakis authored at least 10 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

FuseRank (Demo): Filtered Vector Search in Multimodal Structured Data.

Dimitris Paraschakis, Rasmus Ros, Markus Borg, Per Runeson

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track, 2024

2020

Sociotechnical Aspects of Automated Recommendations: Algorithms, Ethics, and Evaluation.

Dimitris Paraschakis

PhD thesis, 2020

A Bandit-Based Ensemble Framework for Exploration/Exploitation of Diverse Recommendation Components: An Experimental Study within E-Commerce.

Björn Brodén, Mikael Hammar, Bengt J. Nilsson, Dimitris Paraschakis

ACM Trans. Interact. Intell. Syst., 2020

FlowRec: Prototyping Session-Based Recommender Systems in Streaming Mode.

Dimitris Paraschakis, Bengt J. Nilsson

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Matchmaking Under Fairness Constraints: A Speed Dating Case Study.

Dimitris Paraschakis, Bengt J. Nilsson

Proceedings of the Bias and Social Aspects in Search and Recommendation, 2020

2018

Ensemble Recommendations via Thompson Sampling: an Experimental Study within e-Commerce.

Björn Brodén, Mikael Hammar, Bengt J. Nilsson, Dimitris Paraschakis

Proceedings of the 23rd International Conference on Intelligent User Interfaces, 2018

2017

Bandit Algorithms for e-Commerce Recommender Systems: Extended Abstract.

Björn Brodén, Mikael Hammar, Bengt J. Nilsson, Dimitris Paraschakis

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

Towards an ethical recommendation framework.

Dimitris Paraschakis

Proceedings of the 11th International Conference on Research Challenges in Information Science, 2017

2016

Recommender Systems from an Industrial and Ethical Perspective.

Dimitris Paraschakis

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

2015

Comparative Evaluation of Top-N Recommenders in e-Commerce: An Industrial Perspective.

Dimitris Paraschakis, Bengt J. Nilsson, John Hollander

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015