Big Data Analytics: Methods and Applications by Saumyadipta Pyne, B.L.S. Prakasa Rao, S.B. Rao

By Saumyadipta Pyne, B.L.S. Prakasa Rao, S.B. Rao

This booklet has a set of articles written by way of immense facts specialists to explain many of the state of the art tools and purposes from their respective parts of curiosity, and gives the reader with a close evaluate of the sector of massive info Analytics because it is practiced at the present time. The chapters hide technical elements of key parts that generate and use titanic facts corresponding to administration and finance; drugs and healthcare; genome, cytome and microbiome; graphs and networks; net of items; immense facts criteria; bench-marking of structures; and others. as well as assorted functions, key algorithmic techniques equivalent to graph partitioning, clustering and finite combination modelling of high-dimensional facts also are lined. the numerous selection of topics during this quantity introduces the reader to the richness of the rising box of huge facts Analytics.

Show description

Read or Download Big Data Analytics: Methods and Applications PDF

Best data mining books

Transactions on Rough Sets XIII

The LNCS magazine Transactions on tough units is dedicated to the complete spectrum of tough units comparable concerns, from logical and mathematical foundations, via all points of tough set thought and its purposes, comparable to info mining, wisdom discovery, and clever details processing, to kin among tough units and different ways to uncertainty, vagueness, and incompleteness, equivalent to fuzzy units and conception of facts.

Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains

Fresh advancements have tremendously elevated the amount and complexity of information to be had to be mined, prime researchers to discover new how you can glean non-trivial facts immediately. wisdom Discovery Practices and rising functions of knowledge Mining: traits and New domain names introduces the reader to contemporary learn actions within the box of information mining.

Requirements Engineering in the Big Data Era: Second Asia Pacific Symposium, APRES 2015, Wuhan, China, October 18–20, 2015, Proceedings

This booklet constitutes the court cases of the second one Asia Pacific specifications Engineering Symposium, APRES 2015, held in Wuhan, China, in October 2015. The nine complete papers awarded including three device demos papers and one brief paper, have been rigorously reviewed and chosen from 18 submissions. The papers care for quite a few points of necessities engineering within the titanic information period, corresponding to computerized requisites research, specifications acquisition through crowdsourcing, requirement tactics and requirements, requisites engineering instruments.

Extra info for Big Data Analytics: Methods and Applications

Sample text

Major components of an HPCC system include a Thor cluster and a Roxie cluster, although the latter is optional. com. K. Pusala et al. (ETL), as well as linking and indexing massive data from different sources. Roxie is called the query cluster, which is responsible for delivering data for online queries and online analytical processing (OLAP). Similar to Hadoop, HPCC also uses a distributed file system to support parallel processing on Big data. However, compared with HDFS, the distributed file system used by HPCC has some significant distinctions.

To handle such computations on large graphs, the prediction system is developed by using the MapReduce framework and a Hadoop cluster environment. We implemented the MapReduce functions to extract the medical concepts from millions of publications in Medline dataset, to generate the labeled data, and to extract structural features from the large concept graph. Implementing such a graph computation method on MapReduce framework has its own limitations. One of the drawbacks of MapReduce framework is its inability to retain the state of a graph across multiple iterations [44].

Accessed 28 Feb 2015 28. Jayasimha K, Rajyashree M, Tolga K (2013) Large-scale recommendations in a dynamic marketplace. In Workshop on large scale recommendation systems at RecSys 13: 29. Jayasimha K, Rajyashree M, Tolga K (2015) Subjective similarity: personalizing alternative item recommendations. In: WWW workshop: Ad targeting at scale 30. Katukuri JR, Xie Y, Raghavan VV, Gupta A (2012) Hypotheses generation as supervised link discovery with automated class labeling on large-scale biomedical concept networks.

Download PDF sample

Rated 4.15 of 5 – based on 8 votes