A Dynamic Fuzzy Temporal Clustering for Imprecise Location Streams-Reference-Cited by-同舟云学术

A Dynamic Fuzzy Temporal Clustering for Imprecise Location Streams

Published:2017-05-22 Issue:03 Volume:25 Page:409-426
ISSN:0218-4885
Container-title:International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
language:en
Short-container-title:Int. J. Unc. Fuzz. Knowl. Based Syst.

Author:

Quero J. Medina¹,Ruiz Lozano M. D.¹,Castañeda García J. A.²,Rodriguez Molina M. A.²,Frias Jamilena D. M.²

Affiliation:

1. Department of Computer Science and Artificial Intelligence, University of Granada c/. Daniel Saucedo Aranda, 18071 Granada, Spain

2. Department of Marketing and Market Research, University Campus of Cartuja, C.P. 18071 Granada, Spain

Abstract

The clustering has provided data analysis in many contexts of Computer Science. It is widely applied in Ambient Intelligence and Ubiquitous Computing for information processing, with geolocation data prominently. In this paper, we introduce a dynamic fuzzy temporal clustering algorithm (DFTC) to detect stays of users in urban environments based on locations from imprecise sensors. Our approach includes fuzzy evaluation of temporal and probabilistic data providing analysis in real time. As results, we have developed a mobile application which integrates the DFTC and detects satisfactorily user stays related to urban commerces from a real environment.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Information Systems,Control and Systems Engineering,Software

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218488517500179

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