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1,182
From Data Mining to Knowledge Discovery in Databases.
- AI Magazine,
, 1996
"... ■ Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. What is all the excitement about? This article provides an overview of this emerging field, clarifying how data mining and knowledge discovery in database ..."
Abstract
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Cited by 538 (0 self)
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research directions in the field. A cross a wide variety of fields, data are being collected and accumulated at a dramatic pace. There is an urgent need for a new generation of computational theories and tools to assist humans in extracting useful information (knowledge) from the rapidly growing volumes
Search and replication in unstructured peer-to-peer networks
, 2002
"... Abstract Decentralized and unstructured peer-to-peer networks such as Gnutella are attractive for certain applicationsbecause they require no centralized directories and no precise control over network topologies and data placement. However, the flooding-based query algorithm used in Gnutella does n ..."
Abstract
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Cited by 692 (6 self)
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not scale; each individual query gener-ates a large amount of traffic and, as it grows, the system quickly becomes overwhelmed with the query-induced load. This paper explores, through simulation, various alternatives to gnutella's query algorithm, data replicationmethod, and network topology. We
Sciences
"... ......Performance scalability of computing systems built on chip multiprocessor (CMP) multicore architectures is becoming increasingly constrained by limitations in power dissipation, chip packaging, and the data throughput achievable by the interconnection networks. In particular, chip- and package ..."
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......Performance scalability of computing systems built on chip multiprocessor (CMP) multicore architectures is becoming increasingly constrained by limitations in power dissipation, chip packaging, and the data throughput achievable by the interconnection networks. In particular, chip
A Scalable Architecture for e-Science Data Management
"... Abstract—The massive increase in the size of the data provided by e-Science applications requires not only to increase the capabilities of resources, but also to design new strategies for efficient utilization of already available resources. In this paper we present a scalable approach to extend a f ..."
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Cited by 1 (1 self)
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Abstract—The massive increase in the size of the data provided by e-Science applications requires not only to increase the capabilities of resources, but also to design new strategies for efficient utilization of already available resources. In this paper we present a scalable approach to extend a
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 ..."
Abstract
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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
--Preliminary-- Science Data Access Architectures
"... Clearinghouse (ECHO). The OWS provides specifications for accessing digital maps and images, geographic information system (GIS) data and services. The IVOA provides specifications for accessing astrophysics registries, catalogs, data and services. The PDS-OODT system provides servers to access dist ..."
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distributed planetary science registries, catalogs and data. The ECHO system provides a central catalog and order system for accessing distributed collections of earth science data and processing services. These are all "bolt-on " architectures that are added to existing data repositories
An Architecture for Big Data Analytics
"... Big Data is the new experience curve in the new economy driven by data with high volume, velocity, variety, and veracity. They come from various sources that include the Internet, mobile devices, social media, geospatial devices, sensors, and other machine-generated data. Unlocking the value of Big ..."
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Data allows business to better sense and respond to the environment, and is becoming a key to creating competitive advantages in a complex and rapidly changing market. Government is also taking notice of the Big Data phenomenon and has created initiatives to exploit Big Data in many areas
Big Data – The New Science of Complexity
"... Data-intensive techniques, now widely referred to as ‘big data’, allow for novel ways to address complexity in science. I assess their impact on the scientific method. First, big-data science is distinguished from other scientific uses of information technologies, in particular from computer simulat ..."
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Data-intensive techniques, now widely referred to as ‘big data’, allow for novel ways to address complexity in science. I assess their impact on the scientific method. First, big-data science is distinguished from other scientific uses of information technologies, in particular from computer
RDF-3X: a risc-style engine for RDF
- Proc. VLDB Endowment
, 2008
"... ABSTRACT RDF is a data representation format for schema-free structured information that is gaining momentum in the context of Semantic-Web corpora, life sciences, and also Web 2.0 platforms. The "pay-as-you-go" nature of RDF and the flexible pattern-matching capabilities of its query lan ..."
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Cited by 149 (11 self)
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ABSTRACT RDF is a data representation format for schema-free structured information that is gaining momentum in the context of Semantic-Web corpora, life sciences, and also Web 2.0 platforms. The "pay-as-you-go" nature of RDF and the flexible pattern-matching capabilities of its query
Sciences
"... Visual analytic tools are invaluable in the process of knowl-edge discovery. They let us explore datasets intuitively us-ing our eyes. Yet their reliance on human cognitive abilities forces them to be highly interactive. The interactive na-ture of visual analytic systems is facing new challenges wit ..."
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with the emergence of big data. Massive data sizes are pushing against the boundaries of current visualization capabilities. Also the emergence of complex datasets is asking for new ways of navigation in the high–dimensional space. EVA (Ex-plorable Visual Analytics) is an in-progress work for develop-ing a web
Results 1 - 10
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1,182