Paper Info
Title
Rule-based Management of Large Unorganized Data Sets
Abstract
Rule-based systems have been studied for nearly two decades in applications such as geographical information systems (GIS) and metadata catalog systems. Recovering large data sets that are not well organized is a challenge that imposes constraints on applications. These constraints include utilizing huge amounts of memory, consuming excessive amounts of time, and the risk of exceeding these resources, thus causing instability. This work examines a novel approach to provide a large unorganized data set by deriving a rule-based system that regulates web page generation thereby improve cache performance and query generation. The trade-offs imposed by rule-based systems in terms of time to deliver content, memory consumption, and fault tolerance are also analyzed.
Year
DOI
Venue
2012
10.1109/ITNG.2012.66
Information Technology: New Generations
Keywords
Field
DocType
consuming excessive amount,large unorganized data,large data set,memory consumption,rule-based management,web page generation,large unorganized data sets,query generation,geographical information system,rule-based system,fault tolerance,cache performance,databases,knowledge based systems,gis,memory management,rule based system,internet,rule based systems,relational databases,computer science,meta data,rdbms,structured query language,orm,engines,relational database management system
Information system,Data mining,Metadata,Rule-based system,Web page,Computer science,Cache,Knowledge-based systems,Fault tolerance,Memory management,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-1-4673-0798-7
2
0.44
References 
Authors
9
2
Name
Order
Citations
PageRank
Daniel D. Beatty120.44
N Lopez-Benitez2235.66