City Research Online

Identifying Place Histories from Activity Traces with an Eye to Parameter Impact.

Andrienko, G., Andrienko, N., Mladenov, M. , Mock, M. & Pölitz, C. (2011). Identifying Place Histories from Activity Traces with an Eye to Parameter Impact.. IEEE Transactions on Visualization and Computer Graphics, 18(5), pp. 675-688. doi: 10.1109/tvcg.2011.153

Abstract

Events that happened in the past are important for understanding the ongoing processes, predicting future developments, and making informed decisions. Important and/or interesting events tend to attract many people. Some people leave traces of their attendance in the form of computer-processable data, such as records in the databases of mobile phone operators or photos on photo sharing web sites. We developed a suite of visual analytics methods for reconstructing past events from these activity traces. Our tools combine geocomputations, interactive geovisualizations, and statistical methods to enable integrated analysis of the spatial, temporal, and thematic components of the data, including numeric attributes and texts.We also support interactive investigation of the sensitivity of the analysis results to the parameters used in the computations. For this purpose, statistical summaries of computation results obtained with different combinations of parameter values are visualized in a way facilitating comparisons. We demonstrate the utility of our approach on two large real data sets, mobile phone calls in Milano during 9 days and flickr photos made on British Isles during 5 years.

Publication Type: Article
Additional Information: © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords: Event detection, spatio-temporal data, time series analysis, scalable visualization, geovisualization, visual analytics, sensitivity analysis, scale effect
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Science & Technology > Computer Science
School of Science & Technology > Computer Science > giCentre
SWORD Depositor:
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