Header

UZH-Logo

Maintenance Infos

Using 2D Hierarchical Heavy Hitters to Investigate Binary Relationships


Trivellato, Daniel; Mazeika, Arturas; Böhlen, Michael Hanspeter (2008). Using 2D Hierarchical Heavy Hitters to Investigate Binary Relationships. In: Simoff, Simeon J; Böhlen, Michael Hanspeter; Mazeika, Arturas. Visual Data Mining: Theory, Techniques and Tools for Visual Analytics. Berlin / Heidelberg: Springer, 215-235.

Abstract

This chapter presents VHHH: a visual data mining tool to compute and investigate hierarchical heavy hitters (HHHs) for two-dimensional data. VHHH computes the HHHs for a two-dimensional categorical dataset and a given threshold, and visualizes the HHHs in the three dimensional space. The chapter evaluates VHHH on synthetic and real world data, provides an interpretation alphabet, and identifies common visualization patterns of HHHs.

Abstract

This chapter presents VHHH: a visual data mining tool to compute and investigate hierarchical heavy hitters (HHHs) for two-dimensional data. VHHH computes the HHHs for a two-dimensional categorical dataset and a given threshold, and visualizes the HHHs in the three dimensional space. The chapter evaluates VHHH on synthetic and real world data, provides an interpretation alphabet, and identifies common visualization patterns of HHHs.

Statistics

Citations

1 citation in Web of Science®
1 citation in Scopus®
Google Scholar™

Altmetrics

Downloads

187 downloads since deposited on 04 Jun 2012
32 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Book Section, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Date:2008
Deposited On:04 Jun 2012 11:21
Last Modified:05 Apr 2016 15:27
Publisher:Springer
Series Name:Lecture Notes in Computer Science
Number: 4404/2008
ISBN:978-3-540-71079-0
Publisher DOI:https://doi.org/10.1007/978-3-540-71080-6_14
Other Identification Number:merlin-id:2318

Download

Preview Icon on Download
Preview
Content: Accepted Version
Filetype: PDF
Size: 1MB
View at publisher