The advent of the Big Data challenge has stimulated research on methods and techniques to deal with the problem of managing data abundance. As a result, effective sense-making of semantically rich and big datasets has received a lot of attention, and new search approaches, such as Exploratory Computing (EC), have seen the light. In this paper we present IQ4EC, a system for data exploration inspired by EC, that supports users in the inspection of huge amounts of relational data through a step-by-step process, providing feedback based on approximate, intensional information expressed in terms of association rules. At each step of the process, the users can choose a portion of data to examine, and the system guides them to the next step by providing synthetic information and visualization of the resulting dataset.
|Titolo:||IQ4EC: Intensional Answers as a Support to Exploratory Computing|
|Data di pubblicazione:||2015|
|Appare nelle tipologie:||04.01 Contributo in atti di convegno|