short-paper

LOCAl: a personalized cache mechanism for location-based social networks

Authors:

Dimitrios Tomaras,

Ioannis Boutsis,

Vana Kalogeraki,

Dimitrios GunopulosAuthors Info & Claims

SIGSPACIAL '16: Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Article No.: 78, Pages 1 - 4

https://doi.org/10.1145/2996913.2996981

Published: 31 October 2016 Publication History

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Abstract

Recommending nearby Points of Interest (POI) has received growing interest in mobile location-based networks today, where users share content embedded with location information. In this work, we propose a novel caching framework to support personalised proactive caching for mobile location-based social networks. We propose "LOCAI", which uses a probabilistic approach in order to predict the POIs that users will access and retrieve the appropriate data objects that will fulfill user preferences. Our detailed experimental evaluation, using data from the Foursquare location-based social network, illustrates that LOCAI minimizes the user latency to retrieve the data objects they are interested in, is efficient and practical.

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Cited By

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Tomaras D(2018)Crowdsourcing techniques for smart urban mobility2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)10.1109/PERCOMW.2018.8480244(460-461)Online publication date: Mar-2018
https://doi.org/10.1109/PERCOMW.2018.8480244

Index Terms

LOCAl: a personalized cache mechanism for location-based social networks
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles

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Information

Published In

SIGSPACIAL '16: Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

October 2016

649 pages

ISBN:9781450345897

DOI:10.1145/2996913

General Chairs:
Mohamed Ali
University of Washington, Tacoma
,
Shawn Newsam
University of California, Merced
,
Program Chairs:
Matthias Renz
George Mason University, USA
,
Goce Trajcevski
Northwestern University, USA
,
Siva Ravada
Oracle Corporation, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 October 2016

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SIGSPATIAL'16

SIGSPATIAL'16: 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

October 31 - November 3, 2016

California, Burlingame

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SIGSPACIAL '16 Paper Acceptance Rate 40 of 216 submissions, 19%;

Overall Acceptance Rate 220 of 1,116 submissions, 20%

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Tomaras D(2018)Crowdsourcing techniques for smart urban mobility2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)10.1109/PERCOMW.2018.8480244(460-461)Online publication date: Mar-2018
https://doi.org/10.1109/PERCOMW.2018.8480244

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Index Terms

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