Data Exploration and Analytics

Our research focuses on devising and applying data exploration and data analytics algorithms to help various kinds of users to gain insights from their data, letting them understand and interpret data in an investigative way. In particular, we focus on solutions that apply on what is commonly referred to as Big Data, i.e., large amounts of highly heterogeneous data that need to be processed at high-speed.

Query and visualization recommendation

To interactively explore data sets, users profit from some guidance of what to explore next. This requires methods that recommend queries to users that possibly lead users to new facets of the dataset not explored so far. As gaining insight from data is commonly significantly eased through proper visualizations of the data, recommendations of visualizations for the explored data are necessary. In this context, we are researching novel recommendation methods for query and visualization recommendation for data exploration in databases.

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