VAST to Knowledge: Combining tools for exploration and mining

Abstract

The investigation of the VAST Contest collection provided a valuable test for text mining techniques. Our group has focused on creating analytical tools to unveil relevant patterns and to aid with the content navigation in such text collections. Our results show how such an approach, in combination with visualization techniques, can ease the discovery process especially when multiple tools founded on the same approach to data mining are used in complement to and in concert with one another.

An Ontological Framework for Supporting the Design and Evaluation of Visual Analytics Systems

“…[REE * 09], it has always been a challenging undertaking to design, develop, evaluate, and improve VA systems, because of the needs to integrate a range of technologies (e.g., data mining, machine learning, visualization, and human-computer interaction), to respond to the rapid changes of the environments where data is captured, to take advantage of users' knowledge and experience while addressing their cognitive limitations, and often to support mission-critical operations such as emergency and healthcare services. In the VA literature, such challenges have stimulated scholarly discourses on VA workflows [KAF * 08], VA processes [KS11], ensemble tools usage [ALSS07], cognition [GRF08], evaluation [Sch06], collaboration [HA07], insight provenance [GZ08], and so on. This work examines an abstract reasoning methodology behind those discourses on practical design strategies for optimizing different aspects of VA systems.…”

ONTOP - A Process to Support Ontology Conceptualization

“…Even when the set of data is small, an appropriated visualization allows an immediate identification of tenuous differences in the data. Many advantages of visualization uses can be viewed through the researches of many authors (Chen, Kuljis and Paul, 2001) (Auvil, Llorà, Searsmith and Searsmith, 2007) (Ichise, Satoh and Numao, 2008).…”