Titlebook: Big Data Analytics; Third International Srinath Srinivasa,Sameep Mehta Conference proceedings 2014 Springer International Publishing Switz

人類的發(fā)源

HDR-IORT: Physics and Techniquesto address other aspects for the multi-site enterprise such as optimal routing of print jobs and capacity planning. This paper presents a system that can assist the enterprise manager to make efficient job routing decisions within the enterprise. The system described is part of the LDP suite enabling multi-site enterprise print management.

Spinal-Tap

endocardium

URN

Remote Interactive Visualization of Parallel Implementation of Structural Feature Extraction of Thrfeatures of point cloud. Our work includes: (a) parallel implementation a topology-based algorithm for extraction of structural features from lidar point cloud using GPGPU (General Purpose Graphics Processing Unit) computing, and (b) using a LAN (Local Area Network)-based server-client architecture to achieve remote visualization.

護(hù)航艦

Conference proceedings 2014dia, in December 2014. The 11 revised full papers and 6 short papers were carefully reviewed and selected from 35 submissions and cover topics on media analytics; geospatial big data; semantics and data models; search and retrieval; graphics and visualization; application-specific big data.

nephritis

態(tài)度暖昧

MAUVE

Sentiment Analysis of Twitter Feeds,ative and neutral. In particular, we investigate the relevance of using a two-step classifier and negation detection in the space of Twitter Sentiment analysis. An efficient sentiment analyzer is deemed to be a must in the era of big data where preponderance of electronic communication is a major bo

侵害

Graphical Analysis and Visualization of Big Data in Business Domains, Data is actually characterized by the 4V’s – Volume, Variety, Velocity and Veracity. We propose a Big Data Stack and analytics solution that particularly caters to this important problem of addressing Variety and Velocity aspects of data by exploiting inherent relationship among data elements. A un

排名真古怪

Processing Spatio-temporal Data On Map-Reduce,orm, supporting efficient analytics operations over such voluminous datasets become prohibitively expensive. As a result there has been an increasing interest in using map-reduce to parallelize the processing of large-scale spatio-temporal data. While Hadoop, which has become the de-facto implementa