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1,029
The Effect of File Sharing on Record Sales: An Empirical Analysis
- Journal of Political Economy
, 2004
"... numerous seminars, and two anonymous referees for helpful comments. This project would not have been possible without the assistance of several individuals and organizations. MixMasterFlame and the FlameNap network shared P2P data with us, and BigChampagne LLC, the CMJ Network, Nathaniel Leibowitz, ..."
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Cited by 162 (2 self)
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numerous seminars, and two anonymous referees for helpful comments. This project would not have been possible without the assistance of several individuals and organizations. MixMasterFlame and the FlameNap network shared P2P data with us, and BigChampagne LLC, the CMJ Network, Nathaniel Leibowitz
Just how big is global production sharing
- in S. Arndt and H. Kierzkowski (eds), Fragmentation: New Production Patterns in the World
, 2001
"... The sharing of different stages of manufacturing processes between countries is of major and growing importance. However, due to previous deficiencies in the Standard International Trade Classification (SITC) Revision 1 system it was not possible to differentiate between two key elements of this pro ..."
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Cited by 97 (0 self)
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The sharing of different stages of manufacturing processes between countries is of major and growing importance. However, due to previous deficiencies in the Standard International Trade Classification (SITC) Revision 1 system it was not possible to differentiate between two key elements
Data Mining with Big Data
"... Abstract: Big Data concerns large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data is now rapidly expanding in all science and engineering domains, including physical, biological an ..."
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Cited by 34 (0 self)
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and biomedical sciences. This article presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user
on on Biomedical Biomedical
, 2009
"... ncor research national center for ontological PREFACE Ontologies are being used in a variety of ways by researchers in almost every life science discipline, and their use in annotation of both clinical and experimental data is now a common technique in integrative translational research. When data f ..."
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from different sources are described using shared, logically structured, controlled vocabularies such as the Gene Ontology (GO), this makes the data more easily retrievable and navigable, and it also enhances the degree to which they can be analyzed and combined to serve new purposes. Two major
Finding theMissing Link for Big Biomedical Data
"... It has been argued that big data will enable efficien-cies and accountability in health care.1,2 However, to date, other industries have been far more successful at obtaining value from large-scale integration and analy-sis of heterogeneous data sources. What these indus-tries have figured out is th ..."
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is that big data becomes transfor-mative when disparate data sets can be linked at the individual person level. In contrast, big biomedical data are scattered across institutions and intentionally iso-lated to protect patient privacy. Both technical and social challenges to linking these data must
Big Biomedical data as the key resource for discovery science
, 2015
"... Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including i ..."
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Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including
Rateless Codes and Big Downloads
, 2003
"... This paper presents a novel algorithm for downloading big files from multiple sources in peer-to-peer networks. The algorithm is simple, but offers several compelling properties. It ensures low handshaking overhead between peers that download files (or parts of a files) from each other. It is comput ..."
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Cited by 69 (1 self)
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. It is computationally efficient, with cost linear in the amount of data transfered. Most importantly, when nodes leave the network in the middle of uploads, the algorithm minimizes the duplicate information shared by nodes with truncated downloads. Thus, any two peers with partial knowledge of a given file can almost
Software Write Detection for a Distributed Shared Memory
- IN PROCEEDINGS OF THE FIRST USENIX SYMPOSIUM ON OPERATING SYSTEM DESIGN AND IMPLEMENTATION
, 1994
"... Most software-based distributed shared memory (DSM) systems rely on the operating system's virtual memory interface to detect writes to shared data. Strategies based on virtual memory page protection create two problems for a DSM system. First, writes can have high overhead since they are detec ..."
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Cited by 104 (0 self)
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they are detected with a page fault. As a result, a page must be writtenmany times to amortize the cost of that fault. Second, the size of a virtual memory page is too big to serve as a unit of coherency, inducing false sharing. Mechanisms to handle false sharing can increase runtime overhead and may cause data
Toward an ecosystem for precision sharing of segmented Big Data
- in IEEE 6th International Conference on Cloud Computing (CLOUD
, 2013
"... Abstract—As the amount of data created and stored by orga-nizations continues to increase, attention is turning to extracting knowledge from that raw data, including making some data available outside of the organization to enable crowd analytics. The adoption of the MapReduce paradigm has made proc ..."
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Cited by 1 (1 self)
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processing Big Data more accessible, but is still limited to data that is currently available, often only within an organization. Fine-grained control over what information is shared outside an organization is difficult to achieve with Big Data, particularly in the MapReduce model. We introduce a novel
Big Data or Right Data?
"... Big data nowadays is a fashionable topic, independently of what people mean when they use this term. The challenges include how to capture, transfer, store, clean, analyze, filter, search, share, and visualize such data. But being big is just a matter of volume, although there is no clear agreement ..."
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Big data nowadays is a fashionable topic, independently of what people mean when they use this term. The challenges include how to capture, transfer, store, clean, analyze, filter, search, share, and visualize such data. But being big is just a matter of volume, although there is no clear agreement
Results 1 - 10
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1,029