The Mr. DLib team, as part of the ADAPT Centre and Trinity College Dublin, has received funding to hire 2 employees for 2 years to spin-out a business start-up in the field of recommendations-as-a-service and machine learning. The two positions are to be filled with one software architect / product manager and one software engineer, […]
We released version 1.3 of Mr. DLib. 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 in JIRA.
The new version of Mr. DLib completes 104 issues. The most notable ones are: We improved the keyphrase extraction, i.e. keyphrases are no stored differently in Lucene. We expect a better recommendation effectiveness and are currently running an A/B test. More robust path encoding for search queries (special characters in a URL caused errors) Lucene’s eDismax function […]
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 filtering, stereotype, most popular), what […]
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, i.e. JabRef. Currently, Mr. DLib […]
Several new publications: Mr. DLib, Lessons Learned, Choice Overload, Bibliometrics (Mendeley Readership Statistics), Apache Lucene, CC-IDF, TF-IDuF
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. Here is the list: Beel, Joeran, Bela Gipp, and Akiko Aizawa. “Mr. DLib: Recommendations-as-a-Service (RaaS) for Academia.” In Proceedings of the ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL), 2017. Beel, Joeran. “Real-World […]
Stefan Feyer from the University of Konstanz had joined the Mr. DLib team for a six months internship. Yesterday, it was time to say good bye 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 future career and are […]