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MERLIN - A Tool for Multi-party Privacy-preserving Record Linkage

Date

2015

Authors

Ranbaduge, Thilina
Vatsalan, Dinusha
Christen, Peter

Journal Title

Journal ISSN

Volume Title

Publisher

IEEE Computer Society

Abstract

In this paper, we present the current work and future directions on spatiotemporal frequent pattern mining algorithms for mining solar data. The current spatiotemporal pattern mining algorithms focus on spatiotemporal co-occurrence patterns. We reveal four types of spatiotemporal concepts that can be mined from solar data: event sequences, periodicity, spatiotemporal convergence and propagation. Throughout the paper, we exhibit examples of these concepts in the solar physics domain, and present related algorithms and the challenges of mining these concepts from solar data

Description

Keywords

Citation

Source

Efficient Entity Resolution with Adaptive and Interactive Training Data Selection

Type

Conference paper

Book Title

Entity type

Access Statement

License Rights

DOI

10.1109/ICDMW.2015.10

Restricted until

2037-12-31