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big data research papers 2015



An Overview of high-performance parallel Big Data transfers over multiple network channels with Transport Layer Security (TLS) and TLS plus Perfect Forward
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Abstract This Technical Note provides an overview of high-performance parallel Big Data transfers with and without encryption for data in-transit over multiple network channels. It shows that with the parallel approach, it is feasible to carry out high-performance parallel"

Customized Efficient Collection of Big Data for Advertising Services
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Abstract. Because of the advent of smartphones and Internet development, large quantities of data are communicated indiscriminately, thereby generating rapid increases in data traffic. Particularly in the context of social commerce, with its enormous amounts of information,

On site big data analysis system model to promote the competiveness of manufacturing enterprises
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Abstract. Small and medium-sized manufacturing enterprises are highly vulnerable to competition compared to conglomerates, as not many of them have adopted Manufacturing Execution Systems (MES) and do not have sufficient IT specialists and investment funds.

APPLICATION OF BIG DATA IN EDUCATION DATA MINING AND LEARNING ANALYTICS--A LITERATURE REVIEW.
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Abstract The usage of learning management systems in education has been increasing in the last few years. Students have started using mobile phones, primarily smart phones that have become a part of their daily life, to access online content. Student's online activities

Pattern-based Data Sharing in Big Data Environments
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Abstract The staggering growth in Internet of Things (IoTs) technologies is the key driver for generation of massive raw data streams in big data environments. In addition, the collection of raw data streams in big data systems increases computational complexity and resource

Why Big Data Industrial Systems Need Rules and What We Can Do About It
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ABSTRACT Big Data industrial systems that address problems such as classification, information extraction, and entity matching very commonly use hand-crafted rules. Today, however, little is understood about the usage of such rules. In this paper we explore this

Using NVMe Gen3 PCIe SSD Cards in High-density Servers for High-performance Big DataTransfer Over Multiple Network Channels
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Abstract This Technical Note describes how the Zettar team came up with a data transfer cluster design that convincingly proved the feasibility of using high-density servers for high- performance Big Data transfers. It then outlines the tests, operations, and observations

Big Data, IoT,. Buzz Words for Academia or Reality for Industry
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ABSTRACT The concepts of Big Data have became intertwined with those of the Internet of Things, creating mental pictures of a fully connected, all-encompassing, cyber-physical world, where each and every object will contribute with information to a fully aware

What Works for Whom A Bayesian Approach to Channeling Big Data Streams for Policy Analysis June 2015
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Abstract In the coming years, public programs will continuously capture even more and richer data than they do now, including data from web-based tools used by participants in employment services, from tablet-based educational curricula, and from electronic health

OFFICIAL STATISTICS, BIG DATA AND HUMAN DEVELOPMENT
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ABSTRACT This paper aims to contribute to the ongoing and future debate about the relationships between Big Data, official statistics and development primarily by revisiting

The big medical data miss: challenges in establishing an open medical resource
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Laurie Becklund was a noted journalist who died in February 2015 at age 66 from breast cancer. Soon there-after, the Los Angeles Times published her op-ed entitled As I lay dying(REF. 1). She lamented,We are each, in effect, one-person clinical trials. Yet the

Using Big Data to Develop the Epidemiology of Orthopedic Trauma
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The provision of the right data with appropriate quality according to the needs of decision makers or automated processes is crucial for successful operations of companies and government agencies. Management Information Systems, Decision Support Systems,

The Rise of Big Data and Can it be Used to Compare International Healthcare in Orthopaedic Surgery
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In this brief review article I endeavour to give clinicians an understanding of Outcomes Research and briefly describe how it may assist future resource planning. We now live in the era of Big Data, a description of datasets so large and complex that standard or typical

Big data held to privacy laws, too
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Privacy issues around data protection often inspire overengineered responses from scientists and technologists. Yet constraints on the use of personal data mean that privacy is less about what is done with information than what is not done with it. Technology such as

Software Tools and Techniques for Big Data Computing in Healthcare Clouds
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As we delve deeper into the 'Digital Age', we witness an explosive growth in the volume, velocity, and variety of the data available on the Internet. For example, in 2012 about 2.5 quintillion bytes of data was created on a daily basis. The data originated from multiple

Some Flexible Modeling Paradigms for Analyzing Big Data
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Data analysts whether in industry, government, or academia–are faced with increasingly large datasets, or big data. Some examples of discourse on big data include its impact on marketing analytics [1], official statistics [2], and biomedical research [3]. However, when

Big Data Research: Will Industry Solve all the Problems
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Abstract The need for effective tools for big data data management and analytics continues to grow. While the ecosystem of tools is expanding many research problems remain open: they include challenges around efficient processing, flexible analytics, ease of use, and

Data Science, Big Data and Granular Mining
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With the evolution of various modern technologies, huge amount of data is being constantly generated and collected around us. We are in the midst of what is popularly called Information Revolution and are living in a so-called World of Knowledge. Intentionally and/

On Adapting a Military Combat Discrete Event Simulation with Big Data and Geospatial Modeling Toward a Predictive Model Ecosystem for Interpersonal
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Abstract The United States leads industrialized countries in rates of interpersonal violence with homicide being the second leading cause of death for people aged 15 to 24 years. In 2010, more than 4,800 youths (ages 10 to 24) received emergency treatment at hospitals

New perspectives on gathering, vetting and employing Big Data from online social media: An interdisciplinary approach
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Massive textual data sets available in online social media are valuable resources for research in linguistics compared to static corpora in that they offer the possibility of analyzing the temporal unfolding of communication in addition to a wide variety of forms, styles and

Elastic Memory: Bring Elasticity Back to In-Memory Big Data Analytics.
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Abstract Recent big data processing systems provide quick answers to users by keeping data in memory across a cluster. As a simple way to manage data in memory, the systems are deployed as long-running workers on a static allocation of the cluster resources. This

Addressing the Challenges of Teaching Big Data in Technical Education.
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Abstract There is a growing demand for professionals with knowledge of big data and data science. This knowledge can range from data storage, systems infrastructure, to data analytics. The problem in technical education is two-fold: big data is a relatively recent

Tupleware:" Big" Data, Big Analytics, Small Clusters
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targeted and actual users of current analytics frameworks. Most systems are designed for the challenges of the Googles and Facebooks of the world processing petabytes of data distributed across large cloud

GROWING PAINS IN THE ERA OF BIG DATA
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In the five seconds it takes you to read this sentence our global community will have generated another 800 trillion bytes of data. This year alone, the world will add 5 trillion gigabytes that's 5 zettabytes or 5,000,000,000,000,000,000,000 bytes to the ongoing,

A Feature--based Approach to Big Data Medical Image Analysis
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A Feature--based Approach to BigData Medical Image Analysis MaVhew Massive digital memories, rapid data transmission

Big Data Infrastructures: Economics of Resources, Energy, Data, and Applications (Keynote on 2nd Data Storm Summer School 2015)
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Abstract Big data processing infrastructures encompass the full spectrum of cloud-based services: ranging from Infrastructure-as-a-Service (IaaS), to Platform-as-a-Service (Paas) and Data-as-a-Service (DaaS) both for storage as well as processing. Our recent work

Enhanced K-Means++ Clustering For Big Data with Mapreduce
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Abstract Clustering big data using data mining algorithms is a modern approach, used in various science and medical fields. k-means clustering algorithm is a good approach for clustering, but choosing initial centers and provides less accuracy guarantees. The

A Generic Solution to Integrate SQL and Analytics for Big Data
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ABSTRACT There is a need to integrate SQL processing with more advanced machine learning (ML) analytics to drive actionable insights from large volumes of data. As a first step towards this integration, we study how to efficiently connect big SQL systems (either MPP

KNOWLEDGE CLUSTERING ON BIG DATA WITH K_MEANS ALGORITHM
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Abstract-Big Data concerns with large-volume, complex, growing data sets in multiple and autonomous sources. Data storage and Data collection has become more complex. Big Data is now rapidly expanding in all science and engineering domains including physical,

Multi-join Query Evaluation on Big Data Lecture
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Orignally from Romania Had fun with Math: 1976 IMO PhD from University of Pennsylvania: Parallel Query Languages Bell Labs and ATT Labs: Semistructured Data, XML University of Washington: data privacy, probabilistic data, Big Data Dan Suciu Multi-Joins – Lecture

Surveillance, Trust and Big Data The Socio-Legal Relevance of Online Traceability
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Data such as individual traffic data makes many promises indeed, and therefore asks normatively relevant questions of who should have access to it and for what reasons. Never before have we been so measurable by the tools, platforms and infrastructure we depend

The Evolution of Big Data Security through Hadoop Incremental Security Model
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ABSTRACT: Data pours in millions of computers and millions of process every moment of every day so today is the era of Big Data where data interrelate to the volume, velocity, and variety of data interrelate. Huge volume, various varieties and high velocity create lots of Big data enables new directions for scientific research once limited by the volume of available data. For example, many natural language and speech-related problems are ill suited for mathematically precise algorith- mic solutions. To better address this problem, statistical

Similarity Detection via Random Subsets for Cyber War Protection in Big Data using Hadoop Framework
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Abstract The increasing volume of Internet traffic to be analyzed imposes new challenges for anomaly detection systems. These systems should efficiently analyze a large amount of data to discover anomalous fragments within a reasonable response time. In this work, we

The Application Method of CRM as Big Data: Focused on the Car Maintenance Industry
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Abstract. The application direction of the big data should focus on the meaningful information offering for creating the customer. If the car maintenance industry is associated with the big data and the car maintenance record management system can be

Digital Humanities, Big Data, and Literary Studies: Mapping European Literatures in the 21 st Century
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Abstract The purpose of this research is, firstly, to map the 48 national literatures of Europe, through the exploration and the analysis of the bibliographic references contained in the main literary database, the Modern Language Association International Bibliography.

Computational statistics for big data
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Abstract The amount of data stored by organisations and individuals is growing at an astonishing rate. As statistical models grow in complexity and size, traditional machine learning algorithms are struggling to scale well to the large datasets required for model

Small Stories in Big Data: Gaining Insights From Large Spatial Point Pattern Datasets
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Abstract With the onset of big data, it is now relatively easy to gain access to a wide variety and great magnitude of data sources. Data, however, do not necessarily equate to useful insights and meaningful analysis. In this article, we outline a specific step-by-step

From Big Data to Big Service
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Big service brings together both virtual (such as cloud services) and physical (such as public transportation) services; by aggregating these services from various domains it produces composite service solutions to meet customer requirements. Big service is customer

Critical Success Factors (CSFs) of Service-Oriented Architecture (SOA) in BIG DATASystems
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Abstract:The objective of this study is to find out the critical success factors that are needed to implement Service-Oriented Architecture (SOA) in BIGDATA systems such as Cloud Enterprise Resource Planning (CERP) in India. A survey has conducted and data has

A Prototype Implementation of Recommendation Engine Using Big Data Analytics
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ABSTRACT While Big Data is revolutionizing the IT world by solving large dataset problems with performance and scalability, software firms in many sectors are not ready to shift to a wholly Big Data project. The reason being the line of business involves atomic

Broom: sweeping out Garbage Collection from Big Data systems
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Abstract Many popular systems for processing big data are implemented in high-level programming languages with automatic memory management via garbage collection (GC). However, high object churn and large heap sizes put severe strain on the garbage

Big Data: Scale Down, Scale Up, Scale Out
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Page 1. BigData: Scale Down, Scale Up, Scale Out Phillip B. Gibbons Intel Science Technology Center for Cloud Computing Page 3. 4 Phillip B. Gibbons BigData: Scale Down, Scale Up, Scale Out BigData Performance Challenge whenever the volume or velocity of data

Research on IT Architecture of Heterogeneous Big Data
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Abstract The amount of data has grown exponentially in industry and internet, and we are facing a significant problem of information explosion. The challenge is not only to store and manage the vast volume of data (big data), but also to analyze and extract meaningful

Reporting and Big Data. Big Data as one megatrend of industry 4.0 and the impacts on controlling
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The global data volume is expected to increase fiftyfold over the next ten years (2012-2022). Reasons for extensive growth of data volume within the era of industry 4.0 are the increased use of sensor technology in production and logistics as well as the extensive distribution

Adapting bioinformatics curricula for big data
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Abstract Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We

Optique Zooming In on Big Data Access
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Abstract Despite the dramatic growth of data accumulated by enterprises, obtaining value out of it is extremely challenging. In particular, the data access bottleneck prevents domain experts from getting the right piece of data within a constrained time frame. The Optique

Big Data Research
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Contents lists available at ScienceDirect BigData Research bdr Demystifying BigData Analytics for Business Intelligence Through the Lens of Marketing Mix

Causal inference from big data: Theoretical foundations and the data-fusion problem
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We review concepts, principles, and tools that unify current approaches to causal analysis, and attend to new challenges presented by big data. In particular, we address the problem of data-fusion piecing together multiple datasets collected under heterogeneous

CODD: A Dataless Approach to Big Data Testing
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The construction and development of the so-called Big Data systems has occupied centerstage in the data management community in recent years. However, there has been comparatively little attention paid to the testing of such systems, an essential pre-requisite ABSTRACT The motivation for organizing the First IEEE International Conference on Multimedia Big Data (BigMM 2015) was the proliferation of multimedia data and ever- growing requests for multimedia applications, which have made multimedia the" biggest

Harnessing Big Data for Social Good: A Grand Challenge for Social Work
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Despite the technological progress, the social sector has been slow to incorporate a continuous flow of data analytics to inform policy and practice. Because most social program data remain in silos, it is difficult to demonstrate the efficacy and long-term cost benefits of

Big data-a 21st century science Maginot Line No-boundary thinking: shifting from the big data paradigm
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Abstract Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big

Big Progress in Big Data
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All of this data created across the industry lends itself to the concept and tools called big data. The IPI Technology Committee has prepared a timely and relevant presentation on this topic to be shared at many regional parking shows, as well as the 2015 IPI

Tweeting the Olympics: Towards a methodological framework for Big Data analysis of audience engagement during global media events
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Abstract: This article explains the methodological framework created for the 'Tweeting the Olympics' project represented in this Journal issue that can be used and adapted by other researchers in their studies of global media events. This project was a case study in the

Traffic Prediction and Analysis using a Big Data and Visualisation Approach
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Summary This abstract illustrates an approach of using big data, visualisation and data mining techniques used to predict and analyse traffic. The objective is to understand Traffic patterns in Dublin City. The prediction model was used as an estimator to identify unusual

NHIS Big Data and Health Services
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Abstract: Due to rapid ageing, Korea is currently facing senior health issues, including elderly diseases, loss of roles and so on. These increase concerns over ageing well which resolves the problems associated with changes in socio economic structure and improves

Separation, Pooling, and Predictive Privacy Harms from Big Data: Confusing Benefits for Costs
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Privacy is about retarding information flows. It's about being let alone, 1 which boils down to being able to conceal certain details about oneself from the world. In economic jargon, it means to pool. Economists, however, tend to prefer separating to pooling equilibria, as

convergence of big data



Compressing Big Data: when the rate of convergence to the entropy matters.
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Abstract In this talk we discuss of the rate of convergence to the entropy of dictionary based compressors. A faster rate of convergence to the theoretical compression limit should correspond to better compression in practice, but constants also matters. Therefore in the

The 'big data'revolution in healthcare
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a series of converging trends is now bringing the healthcare industry to a tipping point at which bigdata can play a major role, as described in Exhibit 1 . Some of the major forces are described in more detail following the exhibit. Demand Exhibit 1: The convergence of multiple

Extracting value from chaos
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11 The convergence of these developments mobile computing, consumerization of IT, cloud computing, bigdata, and advanced data mining technologies is compelling many organizations to transition from a "chasing compliance" mindset to a risk management mindset.

Bayes and big data: The consensus Monte Carlo algorithm
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There are potential issues with the adequacy of this model, the convergence rate of the MCMC algorithm, and the specific method used to sample In many bigdata problems the analyst is in control of the sharding process, so data can be sharded by randomly assigning each

Big Data Governance
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10. Introduction 11. Retail 12. Oil and Gas 13. Healthcare Convergence of Data Governance, BigData, MDM, BPM Page 5. 2013 Information Asset, LLC sunilsoares@information-asset. com 5 Volume BigData Variety Velocity Volume Data at Rest Data in Motion

MegaODA large sample and BIG DATA time trials: Separating the chaff
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197 All seven time trial experiments run for the large sample are also run for the BIGDATA sample. Optimal Data Analysis, 2, 177-190. Precision and convergence of Monte Carlo estimation of two- category UniODA two-tailed p. Optimal Data Analysis, 1, 43-45. Author Notes

Distribution, Data, Deployment: Software Architecture Convergence in Big Data Systems
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The exponential growth of data in the last decade has fueled a new specialization for software technology, namely that of data-intensive, or big data, software systems [1]. Internet- born organizations such as Google and Amazon are at the cutting edge of this revolution, Cognitive Networked Sensing and BigData Page 2. Cognitive Networked Sensing and BigData Page 3. Page 4. Robert Qiu Michael Wicks Cognitive Networked Sensing and BigData 123 Page 5. Robert Qiu Tennessee Technological University Cookeville, Tennessee, USA

Big Data in Healthcare Hype and Hope
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we researched the coming of BigData to healthcare, and then interviewed, in person, by phone and via email, more than 30 companies in the emerging healthcare BigData ecosystem. . . . . 1 http://www-01.ibm.com/software/data/bigdata/ 2 http

Participatory medicine: a driving force for revolutionizing healthcare
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Healthcare is undergoing a profound revolution as a consequence of three contemporary thrusts: systems medicine [1-4], bigdata and patient involvement in their own health through social networks. This convergence is leading to a medicine that is predictive, preventive, per

The rise of big data spurs a revolution in big analytics
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Data, access to affordable, high-performance hardware, and the emergence of second-generation, analytical tools like Revolution R Enterprise provides greater reasons for stakeholders to invest in Big Analytics. The convergence of these trends means that data analysts need

Cross-country comparisons of wage rates: The Big Mac index
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(1) It is apparent that the data strongly rule out the equality of wage rates measured in a 6 Cumby (1996) suggests that although average deviations from absolute Big Mac parity are large for several currencies, convergence to relative Big Mac parity is quite rapid.

E-business process modeling: the next big step
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Next Big Step Service description provides metalevel data for services and their operations; transport bind- ings tie abstract service descriptions to specific helps in understanding the roles of various standards and in identifying overlaps, gaps, and opportunities for convergence.

Navigating the local modes of big data: The case of topic models
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in dramatically faster convergence. The outline of this chapter is as follows. Finally Section 7 concludes by returning to the constraints and opportunities afforded by bigdata in light of the statistical tools we have to analyze this data. 2 Introduction to Multi-modality

Parallel programming on cloud computing platforms
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Technology Research Association International 23 Abstract:Cloud computing has been very successful in handling bigdata such as in searching engines and database applications.

Partial differential equations for probabilists
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A rigorous approach to convergence theory is combined with an emphasis on applications and practical algorithm design considerations, making this book ideal for researchers in mathematics and computer science, and practitioners in Privacy, BigData, and the Public Good

Real-time big data processing framework: challenges and solutions
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http://dx.doi.org/10.12785/amis/090646 Real-Time BigData Processing Framework: Challenges and Solutions As data has been fundamental resource, how to manage and utilize bigdata better has attracted much attention.

Principal manifolds for data visualization and dimension reduction
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Another big shift of the century is the appearance of the whole framework of machine learning which significantly extends Pearson's initial geometrical approach. 59 2.6. 2 Metabolite Data Analysis.. 76 3.3. 1 Convergence and Cost Functions..

A Brief Overview on Data Mining Survey
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However privacy, security and misuse of information are the big problem if it is not address correctly. Table Description: Figure Name Of Figure Fig.1 Fig.1: Data mining is the core of Knowledge Discovery Process Fig.2 Fig.2: Convergence of three technologies


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