Object structure

Creator:

Shaker, Ammar ; Hüllermeier, Eyke

Contributor:

Kowal, Marek - red. ; Korbicz, Józef - red.

Title:

Survival analysis on data streams: Analyzing temporal events in dynamically changing environments

Subtitle:

.

Group publication title:

AMCS, Volume 24 (2014)

Subject and Keywords:

data streams ; survival analysis ; event history analysis ; earthquake data ; Twitter data

Abstract:

In this paper, we introduce a method for survival analysis on data streams. Survival analysis (also known as event history analysis) is an established statistical method for the study of temporal "events" or, more specifically, questions regarding the temporal distribution of the occurrence of events and their dependence on covariates of the data sources. To make this method applicable in the setting of data streams, we propose an adaptive variant of a model that is closely related to the well-known Cox proportional hazard model. ; Adopting a sliding window approach, our method continuously updates its parameters based on the event data in the current time window. As a proof of concept, we present two case studies in which our method is used for different types of spatio-temporal data analysis, namely, the analysis of earthquake data and Twitter data. In an attempt to explain the frequency of events by the spatial location of the data source, both studies use the location as covariates of the sources.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2014

Resource Type:

artykuł

DOI:

10.2478/amcs-2014-0015

Pages:

199-212

Source:

AMCS, volume 24, number 1 (2014) ; click here to follow the link

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego