Multivariate Time Series Retrieval with Symbolic Aggregate Approximation, Regular Expression, and Query Expansion
Yuncong Yu, Tim Becker, and Michael Behrisch
Committee Laudatio: This paper presents a visual analytics approach to the problem of pattern retrieval from multidimensional time series. The proposed approach is based on symbolic representation, regular expressions and query expansion and is able to effectively deal with pattern distortions across multiple time series. The approach can enable human users to inject their knowledge into the workflow through interactively defining the query and matching characteristics. The paper presents a set of testing results, which convincingly demonstrate the merit of the visual analytics approach.
A Pipeline for Tailored Sampling for Progressive Visual Analytics
Marius Hogräfer, Jakob Burkhardt, and Hans-Jörg Schulz
Committee Laudatio: This paper presents a pipeline for progressive visual analytics in an application, which consists of processes for linearization, subdivision, and selection of data in a large dataset. While the proposed pipeline was designed to address a current need, the idea is promising and the committee believes that it can inspire discussion and further research.
Best Paper Award Committee
University of Maryland
University of Oxford