Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/19155

TitleBuilding a personal symbolic space model from GSM CellID Positioning Data
Author(s)Meneses, Filipe
Moreira, Adriano
KeywordsLocation
GSM
Positioning
Inference
Space model
Issue date28-Apr-2009
PublisherSpringer
JournalLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Abstract(s)The context in which a person uses a mobile context-aware application can be described by many dimensions, including the, most popular, location and position. Some of the data used to describe these dimensions can be acquired directly from sensors or computed by reasoning algorithms. In this paper we propose to contextualize the mobile user of context-aware applications by describing his/her location in a symbolic space model as an alternative to the use of a position represented by a pair of coordinates in a geometric absolute referential. By exploiting the ubiquity of GSM networks, we describe a method to progressively create this symbolic and personal space model, and propose an approach to compute the level of familiarity a person has with each of the identified places. The validity of the developed model is evaluated by comparing the identified places and the computed values for the familiarity index with a ground truth represented by GPS data and the detailed agenda of a few persons.
TypeConference paper
DescriptionSérie : Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 7
URIhttp://hdl.handle.net/1822/19155
ISBN978-3-642-01801-5
978-3-642-01802-2
DOI10.1007/978-3-642-01802-2_23
ISSN1867-8211
1867-822X
Publisher versionhttp://www.springerlink.com/content/w31585762q08v29q/
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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