Dissertation/Thesis Abstract

HRSB-Tree for Spatio-Temporal Aggregates over Moving Regions
by Paduri, Avinash Reddy, M.S., Southern Illinois University at Edwardsville, 2018, 41; 10844304
Abstract (Summary)

Aggregate operations are valuable tools for data analysis in databases. For example, the traditional aggregates like sum, average, count, min and max enable powerful analysis over data in relational databases. Set operations like union, intersection and difference can be used to find aggregate values on spatial, temporal and spatiotemporal data. They take a set of regions, either static or moving, and return a single region. Though there were existing structures to find an aggregate value on spatiotemporal data, they are not efficient to query aggregates on moving regions. This paper proposes a structure that we can use to find different types of aggregates on moving regions.

Indexing (document details)
Advisor: Mckenney, Mark
Commitee: Ercal, Gunes, Yu, Xudong
School: Southern Illinois University at Edwardsville
Department: Computer Science
School Location: United States -- Illinois
Source: MAI 58/03M(E), Masters Abstracts International
Subjects: Computer science
Publication Number: 10844304
ISBN: 978-0-438-76907-6
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