From trajectory modeling to social habits and behaviors analysis

Donatella Gubiani (Author), Marco Pavan (Author)

Abstract

In recent years, the widespread of mobile devices has made easier and popular the activities of recording locations visited by users and of inferring their trajectories. The availability of such large amount of spatio-temporal data opens new challenges to automatically extract information and get valuable knowledge. The many aspects of this issue have aroused the interest of researchers in several areas, such as information retrieval, data mining, context-aware computing, security and privacy issues, urban planning, and transport management. Recently, there has been a strong interest in understanding how people move during their common daily activities in order to get information about their behaviors and habits. In this paper we describe considerable recent research works related to the analysis of mobile spatio-temporal data, focusing on the study of social habits and behaviors. We provide a general perspective on studies on human mobility by depicting and comparing methods and algorithms, highlighting some critical issues related to information extraction from spatio-temporal data, and future research directions.

Keywords

trajectory modeling;social habits;social behaviors;spatio-temporal data;data mining;

Data

Language:	English
Year of publishing:	2017
Typology:	1.16 - Independent Scientific Component Part or a Chapter in a Monograph
Organization:	UNG - University of Nova Gorica
UDC:	004.8
COBISS:	4580347
ISSN:	2198-4190
Views:	4098
Downloads:	0
Average score:	0 (0 votes)
Metadata:

Other data

URN:	URN:SI:UNG
Type (COBISS):	Not categorized
Pages:	Str. 371-385
DOI:	10.1007/978-3-319-40585-8_33
ID:	9226326