The ACM Conference on Recommender Systems (RecSys) is the premier conference to present new research results, systems, and techniques including machine learning and natural language processing relating to recommender systems. This year, the 12th ACM Conference on Recommender Systems takes place in Vancouver, and the call for papers has just been Read more…
From time to time, I get asked by students “how can I find a good PhD supervisor?” And sometimes I sit on PhD evaluation panels and I am surprised how little thought the PhD students put into choosing their supervisor. Therefore, I decided to write this blog post for potential Read more…
Students apparently had a strong focus on the application of machine learning. Students could each distribute 100 points to the different categories, and most students (24% of the points) wanted to learn about machine learning frameworks like scikit-learn, or Tensorflow. However, also a deep understanding of algorithms was demanded (19%). Read more…
The majority of the machine-learning students believed their presentation skills to be average (41%), good (25%) or even excellent (18%). Only a small proportion rated their skills as poor (9%) or very low (7%).
We published a proposal on ResearchGate (DOI: 10.13140/RG.2.2.18759.39842) for a novel approach to the calculate relatedness of research articles and other document types. The relatedness of research articles, patents, legal documents, web pages, and other documents is often calculated with citation or hyperlink based approaches such as citation proximity analysis (CPA). Read more…
According to the students´ self-assessment, they had – on average – average knowledge of JAVA (3.2 out of 5 points). However, there was quite a bit of variance. Many students had very little knowledge of JAVA, while others had excellent knowledge. The knowledge of C/C++/C# was similar to JAVA (3.1 on Read more…
The top careers for the machine-learning students were machine-learning engineer (16%), software engineer (16%), business start-up founder (14%), and data scientist (13%). However, also careers in project management (10%), research (9%) and consultancy (8%) were interesting to some students. “Business manager” was the least attractive career to the machine-learning students. Read more…
On average, the machine-learning students had average knowledge in databases and general writing (around 3 out of 5 points), below-average knowledge in writing research papers (1.9 out of 5 points), and little knowledge in machine learning (1.5 out of 5). The little knowledge about machine learning is not surprising though, Read more…
10% of the students had very low motivation to participate in the module, while the majority of the students had high (28%) or even very high (48%) motivation to learn about machine learning.
Update 2018-07-31: We updated the Dropbox Link Google Scholar recently changed its layout, and as a consequence, Docear couldn’t fetch metadata anymore from Google Scholar for PDF files. Fortunately, one of our users (“Silberzwiebel”) adjusted Docear’s Google Scholar Parser, and now everything works as usual. However, we have not yet integrated 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…
We just returned from the 11th ACM Conference on Recommender Systems in Como, Italy. It was an amazing conference, with lots of interesting presentation relating to recommender systems. One of the hot topics at the Recommender Systems Conference was Deep Learning, though, frankly, deep learning did not always seem to deliver promising Read more…
We published a preprint on arXiv, in which we question the current practice of calculating evaluation metrics for recommender systems as single numbers (e.g. precision p=.28 or mean absolute error MAE = 1.21). We argue that single numbers express only average effectiveness over usually a rather long period (e.g. a Read more…
In the coming term, Prof. Douglas Leith and I will be teaching an introduction to machine learning here at Trinity College Dublin, Ireland. We expect around 200 students, primarily from the new Master of Science in Intelligent System and Data Science. Many students will already have a background in machine 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…
Recently, we spoke with TechCentral.ie, Ireland’s best well-known and respected technology magazine, about recommender systems, personalisation, the challenges of the GDPR and our work in the field of recommender-systems as-a-service and machine learning. The full interview is available here http://www.techcentral.ie/focus-research-joeran-beel-adapt/
We successfully registered the domains recommender-systems.ie and recsys.ie (in addition to our already registered domain recommender-systems.de and domain relating to machine-learning). For now, all domains point to our main website https://ISG.beel.org/. In the long run, we may use these domains for more specific purposes relating to recommender systems. Actually, we hope to 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…
On 28th February, we released version 1.1.1 of Mr. DLib’s recommender system with some minor improvements and bug fixes: Improved 404 error handling for unknown document IDs Fix: The order of authors in the XML was not sorted properly Several internal changes (adjusted logging table; click time is not updated any 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…
Six months ago, we launched Mr. DLib’s recommendations-as-a-service for Academia. Time, to look back and provide some numbers: Since September 2016, Mr. DLib´s recommender system has delivered 60,836,800 recommendations to our partner Sowiport, and Sowiport’s users have clicked 91,545 of the recommendations. This equals on overall click-through rate (CTR) of Read more…
