Presentation of BigDataGrapes at the 12th Recommender Systems Netherlands (RecSysNL) meetup

On 18 December 2018 was held the 12th Recommender Systems Netherlands (RecSysNL) meetup.

The event was hosted by Elsevier, in Amsterdam, Netherlands and concerned two interesting talks, one from industry and one from academia.

The first talk with the title "Mixed-initiative Recommender Systems: Towards a Next Generation of Recommender Systems through User Involvement" presented by Katrien Verbert Associate Professor at the HCI research group of KU Leuven. Katrien Verbert presented her work on interactive visualizations to enable end-users to interact with recommender systems. The objectives were: 1) to explain the rationale of recommendations as a basis to increase user trust and acceptance of recommendations, and 2) to incorporate user feedback and input into the recommendation process and to help steer it. In addition, presented several user studies that investigate how such user controllability interacts with personal characteristics such as expertise and visual working memory.

The second talk with the title "Using heterogenous data to recommend scientific articles and funding opportunities" presented by Finne Boonen and Minh Le who are working on the recommenders team at Elsevier. Their talk was about how Elsevier, as a global information analytics company, drives solutions that approach problems for the scientific community using various big data sources and technologies including machine learning. They for instance, combine click logs, reading history, full-text, and citations using a mixture of recommender system techniques, including learning-to-rank, graph-based keyword extraction, and random walk. In their presentation, they talk through the techniques they have used and their impact in improving researchers’ experience.

In this meetup, the BigDataGrapes project was presented.