Abstract
Big data is a hot topic in research and industry. The availability of data has never been as high as it is now. Making good use of the data is a challenging research topic in all aspects of industry and society. The Bremen Big Data Challenge invites students to dig deep into big data. In this yearly event students are challenged to use the month of March to analyze a big dataset and use the knowledge they gained to answer a question. In this year’s Bremen Big Data Challenge students were challenged to predict the load of the university cafeteria from the load of past years. The best of 24 teams predicted the load with a root mean squared error of 8.6 receipts issued in five minutes, with a fusion system based on the top 5 entries achieving an even better result of 8.28.
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CITATION STYLE
Weiner, J., Diener, L., Stelter, S., Externest, E., Kühl, S., Herff, C., … Schultz, T. (2017). Bremen Big Data Challenge 2017: Predicting University Cafeteria Load. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10505 LNAI, pp. 380–386). Springer Verlag. https://doi.org/10.1007/978-3-319-67190-1_35
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