Scalable linkage across location enhanced services

Date
2017-08
Editor(s)
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
CEUR Workshop Proceedings
Print ISSN
1613-0073
Electronic ISSN
Publisher
CEUR-WS
Volume
Issue
Pages
1 - 4
Language
English
Journal Title
Journal ISSN
Volume Title
Series
Abstract

In this work, we investigate methods for merging spatio-temporal usage and entity records across two location-enhanced services, even when the datasets are semantically different. To address both effectiveness and efficiency, we study this linkage problem in two parts: model and framework. First we discuss models, including κ-l diversity- a concept we developed to capture both spatial and temporal diversity aspects of the linkage, and probabilistic linkage. Second, we aim to develop a framework that brings efficient computation and parallelization support for both models of linkage.

Course
Other identifiers
Book Title
Citation
Published Version (Please cite this version)