FWO: Instant Interactive Data Exploration
Period: 01-2012 → 12-2015
Subgroup: ml
Type: project
People:
- Bart Goethals (UA)
- De Raedt Luc (KU Leuven)
- Tatti Nikolaj (UA)
- Vreeken Jilles (UA)
- Nijssen Siegfried (KU Leuven)
Abstract:
Today, we can easily store massive amounts of information, but we lack the means to exploratively analyse databases of this scale. That is, currently, there is no technology that allows to ‘wander’ around the data, and make discoveries by following intuition, or simple serendipity. While standard data mining is aimed at finding highly interesting results, it is typically computationally demanding and time consuming, and hence not suited for exploring large databases.
To address this problem, we propose to study instant, interactive and adaptive data mining as a new data mining paradigm. Our goal is to study methods that give high-quality (possibly approximate) results instantly, presented understandably, interactively and adaptive as to allow the user to steer the method to the most informative areas in the database rapidly.
Our approach is to develop fast any-time approximation algorithms that allow interactive use. These algorithms learn from the user’s actions, extract constraints from the results the user deems interesting and apply these on different datasets. By interactive visualization, the user quickly grasps results, their place in the data, and can provide feedback to the mining process.
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