A survey on indexing techniques for big data: taxonomy and performance evaluation
The explosive growth in volume, velocity, and diversity of data produced by mobile devices
and cloud applications has contributed to the abundance of data or 'big data.'Available …
and cloud applications has contributed to the abundance of data or 'big data.'Available …
[PDF][PDF] Graph based indexing techniques for big data analytics: a systematic survey
VT Kesavan, BS Kumar - Int. J. Recent Technol. Eng, 2019 - researchgate.net
Big data is a process which is used when the insights and meaning of stored data cannot be
discovered with the existing data mining and handling techniques. The relational database …
discovered with the existing data mining and handling techniques. The relational database …
[PDF][PDF] Distance estimation for very large networks using mapreduce and network structure indices
Distance calculation is key to many network mining applications such as centrality and
clustering. As the size of available networks increases to millions of nodes and edges …
clustering. As the size of available networks increases to millions of nodes and edges …
Estimating graph distance and centrality on shared nothing architectures
We present a parallel toolkit for pairwise distance computation in massive networks.
Computing the exact shortest paths between a large number of vertices is a costly operation …
Computing the exact shortest paths between a large number of vertices is a costly operation …
Decentralized search for shortest path approximation in large-scale complex networks
Finding approximated shortest paths for extremely large-scale complex networks is a
challenging problem, where existing works require large overhead to achieve high accuracy …
challenging problem, where existing works require large overhead to achieve high accuracy …
Detecting Non-Uniform Clusters in Large-Scale Interaction Graphs
Graph clustering becomes difficult as the graph size and complexity increase. In particular,
in interaction graphs, the clusters are small and the data on the underlying interaction are …
in interaction graphs, the clusters are small and the data on the underlying interaction are …
A mapreduce-based parallel clustering algorithm for large protein-protein interaction networks
Clustering proteins or identifying functionally related proteins in Protein-Protein Interaction
(PPI) networks is one of the most computation-intensive problems in the proteomic …
(PPI) networks is one of the most computation-intensive problems in the proteomic …
Algorithm for time-constrained paths to deliver services
R Halonen, O Martikainen, V Naumov… - … on Intelligent Systems …, 2015 - ieeexplore.ieee.org
In logistic services there often are pick-up and delivery time window constraints specified by
logistics customers. Our study was to find a solution to manage huge amount of data to …
logistics customers. Our study was to find a solution to manage huge amount of data to …
Retionomorphic Information Processing for Electrical Epi-Retinal Vision Implant Stimulation
A Schmid - Fourth IEEE Symposium on Bioinformatics and …, 2004 - computer.org
Finding approximated shortest paths for extremely large-scale complex networks is a
challenging problem, where existing works require large overhead to achieve high accuracy …
challenging problem, where existing works require large overhead to achieve high accuracy …
Index-Based Algorithms for Local Query Process in Large-scale Graphs
Z Lu - 2019 - trace.tennessee.edu
Graphs are naturally used to model real-world networks. Among various types of graph,
complex networks, which are a type of graphs (networks) that exhibits unique topology …
complex networks, which are a type of graphs (networks) that exhibits unique topology …