Screenshot of the Homepage of the 1st Interdisciplinary Workshop on Algorithm Selection and Meta-Learning in Information Retrieval (AMIR)

Proposal for the 1st Interdisciplinary Workshop on Algorithm Selection and Meta-Learning in Information Retrieval (AMIR)

Lars Kotthoff and I have applied to organize the 1st Interdisciplinary Workshop on Algorithm Selection and Meta-Learning in Information Retrieval (AMIR) at the 41st European Conference on Information Retrieval (ECIR). Let’s cross fingers and hope it will get accepted. In the following, you find the proposal (also available on ResearchGate as PDF). Read more…

Research-Paper Recommender Systems: A Literature Survey

“Research-Paper Recommender Systems: A Literature Survey” now available open access

“Research-Paper Recommender Systems: A Literature Survey”, our survey on recommender systems for research articles and citations is now available open access on Springer via ReadCube https://rdcu.be/5qT7. This survey is our most cited paper (241 citations according to Google Scholar), and we are glad that it is now available for free for Read more…

Trinity College Dublin seeks to hire a Professor (Chair) in Intelligent Systems

The University of Dublin, Trinity College, invites applications for the position of Professor of Intelligent Systems. The successful candidate will provide strong academic leadership in research, teaching and supervision. The Professor will strengthen the strategic research areas of Artificial Intelligence and Intelligent Content in the School of Computer Science and Read more…

ParsRec: Meta-Learning Recommendations for Bibliographic Reference Parsing (Pre-Print)

We are delighted to announce that our poster “ParsRec: Meta-Learning Recommendations for Bibliographic Reference Parsing” has been accepted at the 12th ACM Recommender Systems Conference (RecSys) for presentation in Vancouver, Canada. The pre-print is available on arXiv, and here in our blog: Abstract Bibliographic reference parsers extract metadata (e.g. author names, Read more…

Click-through rate (CTR) and # of delivered recommendation in JabRef for Mr. DLib’s (MDL) and CORE’s recommendation engine and in total

Mr. DLib’s Living Lab for Scholarly Recommendations (preprint)

We published a manuscript on arXiv about the first living lab for scholarly recommender systems. This lab allows recommender-system researchers to conduct online evaluations of their novel algorithms for scholarly recommendations, i.e., research papers, citations, conferences, research grants etc. Recommendations are delivered through the living lab´s API in platforms such Read more…