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DSC/e Lecture Kai Puolamäki: Human-guided data exploration

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TU/e Zwarte Doos - Filmzaal

Den Dolech 2

Eindhoven

Netherlands

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DSC/e Lecture Series

Speaker:
Kai Puolamäki

Title:
Human-guided data exploration

Doors open at 12:00 h.





We have recently proposed the paradigm of iterative data mining, where the user's current knowledge is modelled by a "background distribution" over the data sets. The user can control the data exploration process by inputting knowledge in the form of patterns observed during the data exploration process using intuitive interactions. These user-defined patterns can be formally expressed as constraints to the background distribution, and new data sets can be sampled from the updated background distribution with computationally efficient constrained randomization scheme. The system then shows the user views of the data that are maximally informative given the user's current knowledge, i.e., where the actual data and the background distribution differ most. Although this scheme is good at showing surprising views of the data to the user, there is a clear shortcoming: the user cannot easily steer the process. In many real cases we want to focus on investigating specific questions concerning the data. Human Guided Data Exploration framework generalizes previous research by allowing the user to interactively compare different complex user-defined hypotheses - which can also be expressed as constraints to the background distribution - about the relations in the data. To showcase the framework, we developed a free open-source tool, using which the empirical evaluation on real-world datasets was carried out. Our evaluation shows that the ability to focus on particular subsets and being able to compare hypotheses are important additions to the interactive iterative data mining process.

Full abstract and biography Kai Puolamäki

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TU/e Zwarte Doos - Filmzaal

Den Dolech 2

Eindhoven

Netherlands

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