A Stream-based Resource for Multi-Dimensional Evaluation of Recommender Algorithms

Benjamin Kille, Andreas Lommatzsch, Frank Hopfgartner, Martha Larson, Arjen P. de Vries

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

4 Citations (Scopus)
44 Downloads (Pure)


Recommender System research has evolved to focus on developing algorithms capable of high performance in online systems. This development calls for a new evaluation infrastructure that supports multi-dimensional evaluation of recommender systems. Today’s researchers should analyze algorithms with respect to a variety of aspects including predictive performance and scalability. Researchers need to subject algorithms to realistic conditions in online A/B tests.
We introduce two resources supporting such evaluation methodologies: the new data set of stream recommendation interactions released for CLEF NewsREEL 2017, and the new Open Recommendation Platform (ORP). The data set allows researchers to study a stream recommendation problem closely by “replaying” it locally, and ORP makes it possible to take this evaluation “live” in a living
lab scenario. Specifically, ORP allows researchers to deploy their algorithms in a live stream to carry out A/B tests. To our knowledge, NewsREEL is the first online news recommender system resource to be put at the disposal of the research community. In order to encourage others to develop comparable resources for a wide range of domains, we present a list of practical lessons learned in the
development of the dataset and ORP.
Original languageEnglish
Title of host publicationProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2017
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery (ACM)
Number of pages4
ISBN (Electronic)978-1-4503-5022-8
Publication statusPublished - 2017
EventSIGIR 2017: 40th International ACM SIGIR Conference on Research and Development in Information Retrieval - Tokyo, Japan
Duration: 7 Aug 201711 Aug 2017


ConferenceSIGIR 2017
Internet address


  • streams
  • recommender system
  • multi--dimensional benchmarking


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