Skip to main navigation
Skip to search
Skip to main content
Arizona State University Home
Home
Profiles
Departments and Centers
Scholarly Works
Activities
Equipment
Grants
Datasets
Prizes
Search by expertise, name or affiliation
A Map-Reduce based parallel approach for improving query performance in a geospatial semantic web for disaster response
Chuanrong Zhang
, Tian Zhao
, Luc Anselin
, Weidong Li
, Ke Chen
Geographical Sciences and Urban Planning, School of (SGSUP)
Spatial Analysis Research Center (SPARC)
Sustainability Initiative
Research output
:
Contribution to journal
›
Article
›
peer-review
14
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'A Map-Reduce based parallel approach for improving query performance in a geospatial semantic web for disaster response'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Spatial Data
100%
Disaster Response
100%
Parallel Approach
100%
MapReduce
100%
Query Performance
100%
Geospatial Semantic Web
100%
Spatial Query
75%
Query Response Time
25%
Impact Area
25%
Full Use
25%
Parallelizing
25%
GeoSPARQL
25%
Emergency Resources
25%
Emergency Powers
25%
Topological Relations
25%
Spatial Ontology
25%
Rapid Retrieval
25%
Task Parallelism
25%
Spatial Join
25%
Geocomputation
25%
Spatial Knowledge Base
25%
Computer Science
Spatial Information
100%
Map-Reduce
100%
Semantic Web
100%
Parallel Approach
100%
Query Performance
100%
Knowledge Base
33%
Query Execution
33%
Ontology
33%
Execution Time
33%
Application Response
33%
Topological Relationship
33%
Parallel Process
33%
Join Computation
33%
Task Parallelism
33%
Information Retrieval
33%