Gravity co-organises the 2nd Budapest RecSys & Personalization Meetup, where on the 9th of June, 2016:
Fabian Abel (Data scientist at XING – the primary social network for business contacts in German-speaking countries, Germany; @fabianabel, http://fabianabel.de/) will talk about the some challenges at XING in conjunction with the RecsysChallenge 2016, co-organized by XING and SZTAKI
- Title: What’s wrong with you, Recruiter-John? A non-trivial recommender challenge.
Alexandros Karatzoglou (Researcher at Telefonica, Spain, @alexk_z, http://www.ci.tuwien.ac.at/~alexis/About.html), will talk about how to leverage deep learning technologies for recommender systems.
- Title: Deep Learning for Recommender Systems
Guy Rapoport (Software Engineer at Dato, US) will talk about Graphlab Create and its recommendation capabilities.
- Title: Practical Recommender Systems Tips
The RecSys Challenge 2016 is co-organized by XING and CrowdRec. RecSys researchers can sign up to participate at: http://2016.recsyschallenge.com
The challenge requires participants to develop algorithm for job recommendation. Given a XING user, the goal is to predict those job postings that a user will click on. The challenge encourages the development of algorithms that are capable of exploiting different sources of information. Participants submit a paper on their solution to the RecSys Challenge Workshop at ACM RecSys 2016.
The 6th RecSysNL meetup will be held on September 28, 2016 starting at 17:30. It will be hosted by ORTEC in Amsterdam, at Condensatorweg 54, 1014 AX Amsterdam.
The RecSysNL Meetup is a meetup for people who are interested in recommender systems, user behavior analytics, machine learning, Artificial Intelligence and all related topics.
CrowdRec partners have released the 30Music Dataset, a collection of listening and playlists data retrieved from Internet radio stations through Last.fm API.
The CLEF initiative (http://www.clef-initiative.eu) continues to promote innovative research on information access systems. CLEF orchestrates a variety of labs each dedicated to a specific challenge for information access systems.
CLEF holds an annual conferences for participants to share ideas and spark new innovation. In 2016, the conference will take place from 5 to 8 September in Evora, Portugal.
Our CrowdRec workshop, devoted to crowdsourcing and human computation for recommender systems, has been accepted to ACM Recommender Systems conference (RecSys), the premier international forum for the presentation of new research results, systems and techniques in the broad field of recommender systems, to be held in Vienna, Austria, from the 16th to 22nd of September, 2015.
>> Submission deadline extended to the 26th of February
A Call for papers for the ACM TIST Special Issue on Crowd in Intelligent Systems has been announced. The ACM Transactions on Intelligent Systems and Technology is a scholarly journal that publishes the highest quality papers on intelligent systems, applicable algorithms and technology with a multi-disciplinary perspective.
The 2014 ACM Conference on Recommender Systems will be taking place in just a few days, and members of CrowdRec will be presenting research results from the project. Below is schedule of all the CrowdRec-related events at RecSys.
On Sept 29th 2014, TUB gave a one day tutorial at Informatik 2014 on how to provide recommendations of streamed data. The Annual Informatik conference is the largest computer science conference series in the German-speaking world. This year, practitioners and scientists will meet in Stuttgart to discuss latest advancements in the field of Big Data.
The CrowdRec project is closely connected to CLEF NEWSREEL, a living lab for benchmarking news recommendations in real-time. CLEF, short for Conference and Labs of Evaluation Form, is one of the main academic campaigns for benchmarking information access systems. Each year, various benchmarking scenarios, referred to as labs, are offered in the context of CLEF.
The NEWSREEL (News Recommendation Evaluation Lab) lab is a benchmarking task that focuses on benchmarking news recommendations in a live data stream of news articles. The lab started a few weeks before the beginning of CrowdRec as an initiative from CrowdRec members of TU Berlin. By participating in NEWSREEL, researchers could evaluate news recommendation techniques over a period of a few months, i.e., the system has been running for the whole duration of CrowdRec. Results were presented in September 2014 at the annual CLEF workshop in Sheffield.
See here for the Overview of CLEF NEWSREEL 2014