Abstract
Real world problems in society, science or economics need human structuring, interpretation and decision making, the limiting factor being the amount of time and effort that the user can invest in the sense-making process. The Dicode data mining services intend to help in clearly defined steps of the sense-making process, where human capacity is most limited and the impact of automatic solutions is most profound. This includes recommendation services to search and filter information, text mining services to search for new information und unknown relations in data, and subgroup discovery services to find and evaluate hypotheses on data. This chapter provides an overview of the data mining services developed in the context of the Dicode project. It addresses the usability of the services and indicates which big data technologies are being used to deal with very large data collections.
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Notes
- 1.
Developers interested in using the statistics might have a look at Max Jacob’s talk at the Berlin Buzzwords Conference 2012 which explains the extraction of Wikipedia statistics in detail: http://vimeo.com/45123391.
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Friesen, N. et al. (2014). The Dicode Data Mining Services. In: Karacapilidis, N. (eds) Mastering Data-Intensive Collaboration and Decision Making. Studies in Big Data, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-02612-1_5
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DOI: https://doi.org/10.1007/978-3-319-02612-1_5
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