Author, as appears in the article.: Al-Molegi, Abdulrahman; Alsmadi, Izzat; Martinez-Balleste, Antoni;
Department: Enginyeria Informàtica i Matemàtiques
URV's Author/s: Martínez Ballesté, Antoni
Keywords: Regions-of-interest discovering People movement Markov chain Location-based services Location prediction
Abstract: Abstract Location-Based Services (LBSs) provide users especially in smartphones with information and services based on their location and interests. Predicting people’s next location could help in improving the quality of such services and, in turn, boosting people’s confidence on those services. Any successful LBS algorithm or model should target three major goals: Location prediction accuracy, high throughput or fast response and efficiency in terms of utilizing smartphone resources. This paper proposes a new approach to discover and predict people’s next location based on their mobility patterns, while being computationally efficient. The approach starts by discovering Regions-of-Interest (RoIs) in people’s historical trajectories (which denote the locations where users have been previously, frequently). A new model based on Markov Chain (MC) is proposed to overcome the drawback of classical MC. Our …
Thematic Areas: Telecommunications Software Information systems Hardware and architecture Computer science, information systems Computer science applications Computer science (miscellaneous) Computer networks and communications Ciência da computação Applied mathematics
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: antoni.martinez@urv.cat
Author identifier: 0000-0002-1787-7410
Record's date: 2024-08-31
Papper version: info:eu-repo/semantics/acceptedVersion
Link to the original source: https://www.sciencedirect.com/science/article/abs/pii/S1574119217303632?via%3Dihub
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Pervasive And Mobile Computing. 47 31-53
APA: Al-Molegi, Abdulrahman; Alsmadi, Izzat; Martinez-Balleste, Antoni; (2018). Regions-of-interest discovering and predicting in smartphone environments. Pervasive And Mobile Computing, 47(), 31-53. DOI: 10.1016/j.pmcj.2018.05.001
Article's DOI: 10.1016/j.pmcj.2018.05.001
Entity: Universitat Rovira i Virgili
Journal publication year: 2018
Publication Type: Journal Publications
Repositori URV