This project is an extension of i2MapReduce: Incremental MapReduce for Mining Evolving Big Data . i2MapReduce is used for incremental big data processing, which uses a fine-grained incremental engine, a general purpose iterative model that includes iteration algorithms such as PageRank, Fuzzy-C-Means(FCM), Generalized Iterated Matrix-Vector Multiplication(GIM-V), Single Source Shortest Path(SSSP). The main purpose of this project is to reduce input/output overhead, to avoid incurring the cost of re-computation and avoid stale data mining results. Finally, the performance of i2MapReduce is analyzed by comparing the resultant graphs
This is an extended version of Modeling Big Data Processing Programs, by Joao Batista de Souza Neto,...
Abstract—The growing computerization in modern academic and industrial sectors is generating huge vo...
Large datasets (“Big Data”) are becoming ubiquitous be-cause the potential value in deriving insight...
Abstract—As new data and updates are constantly arriving, the results of data mining applications be...
Cloud intelligence applications often perform iterative computa-tions (e.g., PageRank) on constantly...
Abstract: Data mining is the application of specific algorithms for extracting patterns from data. B...
Big Data -A, an acceleration framework that optimizes Big Data with plug-in components for fast data...
With the continuous development of the Internet and information technology, more and more mobile ter...
With the ease of access to connected devices and online services, data of a wide variety are constan...
Big-data is an excellent source of knowledge and information from our systems and clients, but de...
The aim of this paper is to present advanced methods for the search for new knowledge contained in B...
We are now in Big Data era, and there is a growing demand for tools which can process and analyze it...
The term `big data analytics' emerged in order to engage in the ever increasing amount of scientific...
2 Course Contents Statistics provide the theoretical foundation to compute supervised and unsupervis...
A massive bulk of data is being created due to digitalisation in various industries, including medic...
This is an extended version of Modeling Big Data Processing Programs, by Joao Batista de Souza Neto,...
Abstract—The growing computerization in modern academic and industrial sectors is generating huge vo...
Large datasets (“Big Data”) are becoming ubiquitous be-cause the potential value in deriving insight...
Abstract—As new data and updates are constantly arriving, the results of data mining applications be...
Cloud intelligence applications often perform iterative computa-tions (e.g., PageRank) on constantly...
Abstract: Data mining is the application of specific algorithms for extracting patterns from data. B...
Big Data -A, an acceleration framework that optimizes Big Data with plug-in components for fast data...
With the continuous development of the Internet and information technology, more and more mobile ter...
With the ease of access to connected devices and online services, data of a wide variety are constan...
Big-data is an excellent source of knowledge and information from our systems and clients, but de...
The aim of this paper is to present advanced methods for the search for new knowledge contained in B...
We are now in Big Data era, and there is a growing demand for tools which can process and analyze it...
The term `big data analytics' emerged in order to engage in the ever increasing amount of scientific...
2 Course Contents Statistics provide the theoretical foundation to compute supervised and unsupervis...
A massive bulk of data is being created due to digitalisation in various industries, including medic...
This is an extended version of Modeling Big Data Processing Programs, by Joao Batista de Souza Neto,...
Abstract—The growing computerization in modern academic and industrial sectors is generating huge vo...
Large datasets (“Big Data”) are becoming ubiquitous be-cause the potential value in deriving insight...