Fraunhofer-Gesellschaft

Publica

Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

A benchmark for content-based retrieval in bivariate data collections

 
: Scherer, Maximilian; Landesberger, Tatiana von; Schreck, Tobias

:

Zaphiris, Panayiotis (Ed.):
Theory and practice of digital libraries. Second international conference, TPDL 2012 : Paphos, Cyprus, September 23 - 27, 2012; proceedings
Berlin: Springer, 2012 (Lecture Notes in Computer Science 7489)
ISBN: 978-3-642-33289-0
ISBN: 978-3-642-33290-6
ISBN: 3-642-33289-7
ISSN: 0302-9743
pp.286-297
International Conference of Theory and Practice of Digital Libraries (TPDL) <2, 2012, Paphos/Cyprus>
English
Conference Paper
Fraunhofer IGD ()
visual analytic; Digital Library; information retrieval; Benchmarking; content based retrieval; feature extraction; Forschungsgruppe Visual Search and Analysis (VISA)

Abstract
Huge amounts of various research data are produced and made publicly available in digital libraries. An important category is bivariate data (measurements of one variable versus the other). Examples of bivariate data include observations of temperature and ozone levels (e.g., in environmental observation), domestic production and unemployment (e.g., in economics), or education and income level levels (in the social sciences). For accessing these data, content-based retrieval is an important query modality. It allows researchers to search for specific relationships among data variables (e.g., quadratic dependence of temperature on altitude). However, such retrieval is to date a challenge, as it is not clear which similarity measures to apply. Various approaches have been proposed, yet no benchmarks to compare their retrieval effectiveness have been defined.
In this paper, we construct a benchmark for retrieval of bivariate data. It is based on a large collection of bivariate research data. To define similarity classes, we use category information that was annotated by domain experts. The resulting similarity classes are used to compare several recently proposed content-based retrieval approaches for bivariate data, by means of precision and recall. This study is the first to present an encompassing benchmark data set and compare the performance of respective techniques. We also identify potential research directions based on the results obtained for bivariate data. The benchmark and implementations of similarity functions are made available, to foster research in this emerging area of content-based retrieval.

: http://publica.fraunhofer.de/documents/N-238376.html