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Local patterns, like itemsets, correlations, contrast sets or subgroups, stand out from other data mining tools by their descriptive nature, which makes them directly interpretable by end users like clinicians, fraud experts or analysts. In this workshop, we wish to investigate typical use cases and key requirements for the successful usage of local pattern mining in applications where next to the statistical performance of models, the understandability and interestingness of the models is the key success factor.

Submissions due: June 29, 2012

The first scientific Dicode workshop, namely "dicoSyn 2012: Mastering Data-Intensive Collaboration through the Synergy of Human and Machine Reasoning" (http://dicode.cti.gr/dicosyn12/) took place in Seattle, in the context of CSCW 2012 (Feb 12, 2012). Eight papers were presented, thus bringing together researchers and practitioners from different scientific fields and research communities to further explore the synergy between human and machine intelligence.

Contemporary collaboration settings are often associated with huge, ever-increasing amounts of multiple types of data, which may vary in terms of relevance, subjectivity and importance, ranging from individual opinions to broadly accepted practices. In such settings, collective sense making is crucial for well-informed decision making. This sense making process may both utilize and provide input to intelligent information analysis tools.

The paper entitled “Building on the synergy of machine and human reasoning to tackle data-intensive collaboration and decision making” (authored by Nikos Karacapilidis, Stefan Rüping, Manolis Tzagarakis, Axel Poigné and Spyros Christodoulou), which reports on the Dicode approach, was judged worthy of the “Best Research Paper Award” at the KES 3rd International Conference on Intelligent Decision Technologies (July 2011, Piraeus, Greece).