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ODAM: An optimized distributed association rule mining algorithm
TLDR
This work has developed a distributed algorithm, called optimized distributed association mining, for geographically distributed data sets, called ODAM, which generates support counts of candidate itemsets quicker than the other DARM algorithms and reduces the size of average transactions, data set, and message exchanges.
k-Nearest Neighbors on Road Networks: A Journey in Experimentation and In-Memory Implementation
TLDR
An extensive experimental investigation in main memory revisits a previously discarded technique (IER) showing that, through a simple improvement, it is often the best performing technique.
High Performance Parallel Database Processing and Grid Databases
This book targets the theoretical/conceptual details needed to form a base of understanding and then delivers information on development, implementations, and analytical modeling of parallel
Domain-Driven, Actionable Knowledge Discovery
TLDR
Data mining increasingly faces complex challenges in the real-life world of business problems and needs and both researchers and practitioners are realizing the importance of domain knowledge to close this gap and develop actionable knowledge for real user needs.
A distributed approach to sub-ontology extraction
TLDR
This paper proposes an approach for distributed ontology extraction where each user may extract optimized sub-ontologies from an existing base ontology, knowing that this approach will play an important role in improving the efficiency of information retrieval.
Semantic Completeness in Sub-ontology Extraction Using Distributed Methods
TLDR
A distributed memory architecture serves two purposes: Facilitates the utilization of a cluster environment typical in business organizations, which is in line with the envisaged application of the proposed system and enhances the performance of the computationally extensive extraction process when dealing with massively sized realistic ontologies.
Aggregate-join query processing in parallel database systems
TLDR
Three parallel aggregate-join query processing methods are discussed, namely: Join Partition Method (JPM), Aggregate Partitions Method (APM), and Hybrid Partition method (HPM), which use the join attribute and the group-by attribute, respectively, as the partitioning attribute.
Continuous Range Search Query Processing in Mobile Navigation
TLDR
This paper proposes two new methods to process continuous range search query in mobile computing, one is constructed using R-tree index based on Euclidean distance, and the other addresses the requirement on actual network distance.
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