DENCAST: distributed density-based clustering for multi-target regression
Recent developments in sensor networks and mobile computing led to a huge increase in
data generated that need to be processed and analyzed efficiently. In this context, many …
data generated that need to be processed and analyzed efficiently. In this context, many …
Distributed graph cube generation using Spark framework
Graph OLAP is a technology that generates aggregates or summaries of a large-scale graph
based on the properties (or dimensions) associated with its nodes and edges, and in turn …
based on the properties (or dimensions) associated with its nodes and edges, and in turn …
Cymbalo: An efficient graph processing framework for machine learning
Due to the growth of data scale, distributed machine learning has become more important
than ever. Some recent work, like TuX^ 2, show promising prospect in dealing with …
than ever. Some recent work, like TuX^ 2, show promising prospect in dealing with …
Graphduo: A dual-model graph processing framework
Algorithms for large-scale natural graph processing can be categorized into two types based
on their value propagation behaviors: the unidirectional value propagation algorithms and …
on their value propagation behaviors: the unidirectional value propagation algorithms and …