We were accepted for publication at ComplexRec 2019, the third workshop on Recommendation in Complex Scenarios at the 13th ACM Recommender Systems Conference (RecSys 2019) in Copenhagan, Denmark. Abstract. effectiveness of recommender system algorithms varies in different real-world scenarios. It is difficult to choose a best algorithm for a scenario Read more…
Our paper “Document Embeddings vs. Keyphrases vs. Terms: An Online Evaluation in Digital Library Recommender Systems” was accepted for publication at the ACM/IEEE Joint Conference on Digital Libraries. 1 Introduction Many recommendation algorithms are available to operators of recommender systems in digital libraries. The effectiveness of algorithms in real-world systems is Read more…
Our paper “A Novel Approach to Recommendation Algorithm Selection using Meta-Learning” was accepted for publication at the 26th Irish Conference on Artificial Intelligence and Cognitive Science (AICS): Introduction The ‘algorithm selection problem’ describes the challenge of finding the most effective algorithm for a given recommendation scenario. Some typical recommendation scenarios are Read more…
We recently had a paper accepted to iConference. We used click data from Mr DLib, our recommender-as-a-service, to see if users of recommender systems in digital libraries are affected by position bias. We found that users are affected by position bias on average. Some users do seem to examine recommendations Read more…