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…
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…
We released version 1.3 of Mr. DLib´s Recommender-System as-a-Service. The new major feature is “word embeddings” based recommendations. We are excited to see how the new recommendations will perform with our partners. In addition, we fixed many small bugs, and added some minor improvements. A complete overview can be found Read more…
The new version of our recommender system completes 104 issues and significantly improves the recommendations. The most notable improvements are: We improved the keyphrase extraction process in the recommender system, i.e. keyphrases are not stored differently in Lucene. We expect better recommendation effectiveness and are currently running an A/B test. More Read more…
We are proud to announce the release of ‘RARD’, the related-article recommendation dataset from the digital library Sowiport and the recommendation-as-a-service provider Mr. DLib. The dataset contains information about 57.4 million recommendations that were displayed to the users of Sowiport. Information includes details on which recommendation approaches were used (e.g. content-based Read more…
There are two major news coming along with the new version of Mr. DLib’s Recommendation API. JabRef finally uses Mr. DLib for it’s recommender system We have announced this already a while ago, but now, finally, Mr. DLib’s recommendations are available in one of the most popular open-source reference managers, Read more…
In the past few weeks, we published (or received acceptance notices for) a number of papers related to Mr. DLib, research-paper recommender systems, and recommendations-as-a-service. Many of them were written during our time at the NII or in collaboration with the NII. Here is the list of publications: Beel, Joeran, Bela Gipp, Read more…
Stefan Feyer from the University of Konstanz had joined the Mr. DLib team for a six months internship. Yesterday, it was time to say goodbye to Stefan and we had a small farewell party at the National Institute of Informatics (NII) in Tokyo. We wish Stefan all the best for his Read more…