Prof Dr Joeran Beel and his team are part of the ADAPT Research Centre as well as of the School of Computer Science and Statistics at Trinity College Dublin. Our work focuses on machine learning, text mining, natural language processing, the blockchain and other technologies, in areas including recommender systems, search engines, news analysis, plagiarism detection, and machine translation. Domains we are particularly interested in include digital libraries & digital humanities, health care, tourism, law, fintech, and transportation. If you want to lean more about our research on recommender systems as a service, read our blog posts below, or have a look at our research areas, industry partner page, or homepage.
Our manuscript “The Architecture of Mr. DLib’s Scientific Recommender-System API” got accepted at the “26th Irish Conference on Artificial Intelligence and Cognitive Science” (AICS), and here is the pre-print version (HTML below; PDF on arxiv). The bibliographic BibTeX data is: @InProceedings{Beel2018MDLArch, author = {Beel, Joeran and Collins, Andrew and Aizawa, 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…