Mr. DLib: Recommender-System As-a-Service (Recommender Systems Dublin)

Mr. DLib v1.2.1: Improved keyphrase recommendations and Apache Lucene query handling

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…

Mr. DLib v1.1 released: JavaScript Client, 15 million CORE documents, new URL for recommendations-as-a-service via title search

We are proud to announce version 1.1 of Mr. DLib’s Recommender-System as-a-Service. The major new features are: A JavaScript Client to request recommendations from Mr. DLib. The JavaScript offers many advantages compared to a server-side processing of our recommendations. Among others, the main page will load faster while recommendations are requested in the Read more…

Docear 1.0.3 Beta: rate recommendation, new web interface, bug fixes, …

Update: February 18, 2014: No bugs were reported, as such we declare Docear 1.03 with its recommender system as stable. It can be downloaded on the normal download page.


With Docear 1.0.3 beta we have improved PDF handling, the recommender system, provided some help for new users and enhanced the way how you can access your mind maps online.

PDF Handling

We fixed several minor bugs with regard to PDF handling. In previous versions of Docear, nested PDF bookmarks were imported twice when you drag & dropped a PDF file to the mind map. Renaming PDF files from within Docear changed the file links in your mind maps but did not change them in your BibTeX file. Both issues are fixed now. To rename a PDF file from within Docear you just have to right-click it in Docear’s workspace panel on the left hand side and it is important that the mind maps you have linked the file in, are opened. We know, this is still not ideal, and will improve this in future versions of Docear.

Rate Your Recommendations

You already know about our recommender system for academic literature. If you want to help us improving it, you can now rate how good a specific set of recommendations reflects your personal field of interest. Btw. it would be nice if you do not rate a set of recommendations negatively only because it contains some recommendations you received previously. Currently, we have no mechanism to detect duplicate recommendations.

rate a literature recommendation set

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