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词汇 example_english_big-data
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Examples of big data


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The resulting 'bigdata' offers the statistical power needed to discover which tutorial actions help which students in which cases.
Hearst is a leading expert in the area of user interfaces for search engine technology and bigdata analytics.
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Personal has helped to popularize the concept of small data, which it defines as bigdata for the benefit of individuals.
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Its products deal with problems sometimes called bigdata.
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E-science encompasses what is often referred to as bigdata which has revolutionized science...
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It is a bigdata company that uses location data to drive superior ad targeting across mobile devices.
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Vast amount of sensory data in addition to historical data construct the bigdata in manufacturing.
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Bigdata sizes are a constantly moving target, ranging from a few dozen terabytes to many petabytes of data in a single data set.
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These qualities are not consistent with bigdata analytics systems that thrive on system performance, commodity infrastructure, and low cost.
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The cloud is used for providing a scalable way of streaming the game content and bigdata analysis.
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This makes it one of the world's top five bigdata processing organizations and owner of the world's largest media consumption data sets.
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The rise of bigdata resulted in many traditional data warehousing companies updating their products and technology.
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As such, there is some overlap with bigdata, international development, and community engagement.
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The bigdata sets are mined for use in predictive analytics which allow the company to optimize operations by predicting customer's habits.
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The discussion examined the influence of bigdata, the rise of technology, and the evolving competitive advantage analytics provides.
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Wikibon creates and shares infographics, and covers topics such as cloud computing, bigdata, and virtualization on its blog.
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Among other things, he has been studying data privacy, governance in virtual worlds, law and entrepreneurship, e-government, and (most recently) bigdata.
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The collaborative is made up primarily of women working within privacy, surveillance, code, bigdata research, art and critical culture.
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The term bigdata is about machines and small data is about people.
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The challenge for large enterprises is determining who should own bigdata initiatives that straddle the entire organization.
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Multidimensional bigdata can also be represented as tensors, which can be more efficiently handled by tensor-based computation, such as multilinear subspace learning.
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Real or near-real time information delivery is one of the defining characteristics of bigdata analytics.
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Recent studies show that the use of a multiple layer architecture is an option for dealing with bigdata.
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Many of the techniques used in computational law are taken or derived from techniques in the domains of natural language processing and bigdata analysis.
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Unfortunately, bigdata studies requires a faster algorithm with still acceptable success.
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While bigdata typically presents challenges in its information volume, variety and velocity, social media presents a fourth: establishing veracity.
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Another stream of research currently focuses on aspects of bigdata in health information systems.
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The company develops customer service-based software that focuses on bigdata, predictive analytics, and real-time decisioning.
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He now focuses on high performance computing and bigdata in the cloud.
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He is a computational social scientist focussing on analysis and prediction of social and financial complexity captured in bigdata.
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In the past few years, main topics have been related to cloud computing, distributed computing, virtualization, minimizing downtime, bigdata, and information technology.
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It houses about 200 scientists and engineers, some of whom work on bigdata computing.
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The information society will process more and more data, and we need efficient instruments to deal with the bigdata.
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Bigdata provides an infrastructure for transparency in manufacturing industry, which is the ability to unravel uncertainties such as inconsistent component performance and availability.
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As a response to this critique it has been suggested to combine bigdata approaches with computer simulations, such as agent-based models, for example.
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The methodology addresses handling bigdata in terms of useful permutations of data sources, complexity in interrelationships, and difficulty in deleting (or modifying) individual records.
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This bigdata is one of the primary reasons it has become important to collect, process and analyze data efficiently and accurately.
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The techniques rely heavily on user interaction and the human visual system, and exist in the intersection between visual analytics and bigdata.
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The acquisition was promoted using the marketing term bigdata.
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Using techniques of bigdata analytics, researchers can receive recommendations on relevant opportunities based on their profiles.
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Since the year 2011, this term is now referred to as bigdata by industry.
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Bigdata analysis technologies make it possible to perform controlled experiments to test hypotheses and analyze results to discover complex correlations.
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Achieving the potential of bigdata driven demand modeling requires integrating this data to find correlations across the organization and marketplace.
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Such data sets are commonly referred to as bigdata.
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The data placement structure and its implementation presented in the paper have been widely adopted in the open source community, bigdata analytics industries, and application users.
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The company offers state-of-the-art artificial intelligence with multi-dimensional sensing and motion control to help companies automate processes, from making machines more flexible to analyzing bigdata.
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The results hint that there may potentially be a relationship between the economic success of a country and the information-seeking behavior of its citizens captured in bigdata.
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It specializes in innovative and scalable cluster, storage and networking products developed for data center, high performance computing, cloud and bigdata applications for corporate, scientific, military and government use.
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Moreover, they proposed an approach for identifying the encoding technique to advance towards an expedited search over encrypted text leading to the security enhancements in bigdata.
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Advancements in bigdata analysis offer cost-effective opportunities to improve decision-making in critical development areas such as health care, employment, economic productivity, crime, security, and natural disaster and resource management.
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He is known for his research contributions in artificial intelligence, machine learning, data mining, knowledge representation, neural networks, semantic web, bigdata analytics, and bioinformatics and computational biology.
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The global healthcare issues chosen for 2013 are: obesity, mental health, accountable care, end-of-life care, road traffic injury, patient engagement, antimicrobial resistance, and bigdata and healthcare.
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Most of these bigdata are multidimensional.
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Recent developments in bigdata analysis, combined with graph mining techniques, make it possible to analyze petabytes of structured and unstructured information and feed user-facing applications.
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What will the bigdata bring us?
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The subject is not restricted to only bigdata, although the fact that data is scaling up makes bigdata an important aspect of data science.
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These examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors.
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