Results 271 to 280 of about 25,310,122 (328)
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Diamond Sketch: Accurate Per-flow Measurement for Big Streaming Data
IEEE Transactions on Parallel and Distributed Systems, 2019Per-flow measurement is a critical issue in computer networks, and one of its key tasks is to count the number of packets in each flow (for big streaming data).
Tong Yang +5 more
semanticscholar +1 more source
21st International Conference on Data Engineering (ICDE'05), 2003
This tutorial provides a comprehensive and cohesive overview of the key research results in the area of data stream query processing, both for SQL-like and XML query languages.
N. Koudas, D. Srivastava
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This tutorial provides a comprehensive and cohesive overview of the key research results in the area of data stream query processing, both for SQL-like and XML query languages.
N. Koudas, D. Srivastava
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2009
Nowadays, data bases are required to store massive amounts of data that are continuously inserted, and queried. Organizations use decision support systems to identify potential useful patterns in data. Data analysis is complex, interactive, and exploratory over very large volumes of historic data, eventually stored in distributed environments.
João Gama, Pedro Pereira Rodrigues
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Nowadays, data bases are required to store massive amounts of data that are continuously inserted, and queried. Organizations use decision support systems to identify potential useful patterns in data. Data analysis is complex, interactive, and exploratory over very large volumes of historic data, eventually stored in distributed environments.
João Gama, Pedro Pereira Rodrigues
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International Conference on Machine Learning and Applications, 2019
With the Internet of Things (IoT) devices becoming an integral part of human life, the need for robust anomaly detection in streaming data has also been elevated.
Mohsin Munir +3 more
semanticscholar +1 more source
With the Internet of Things (IoT) devices becoming an integral part of human life, the need for robust anomaly detection in streaming data has also been elevated.
Mohsin Munir +3 more
semanticscholar +1 more source
From Streaming Data to Streaming Insights
Proceedings of the 2014 Workshop on Human Centered Big Data Research, 2014The rise of Big Data has influenced the design and technical implementation of visual analytic tools required to handle the increased volumes, velocities, and varieties of data. This has required a set of data management and computational advancements to allow us to store and compute on such datasets.
Alex Endert +2 more
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IEEE Transactions on Cybernetics, 2019
In this article, we propose an online and unsupervised anomaly detection algorithm for streaming data using an array of sliding windows and the probability density-based descriptors (PDDs) (based on these windows). This algorithm mainly consists of three
Lingyu Zhang, Jiabao Zhao, Wei Li
semanticscholar +1 more source
In this article, we propose an online and unsupervised anomaly detection algorithm for streaming data using an array of sliding windows and the probability density-based descriptors (PDDs) (based on these windows). This algorithm mainly consists of three
Lingyu Zhang, Jiabao Zhao, Wei Li
semanticscholar +1 more source
Streaming Queries over Streaming Data
2002Recent work on querying data streams has focused on systems where newly arriving data is processed and continuously streamed to the user in real-time. In many emerging applications, however, ad hoc queries and/or intermittent connectivity also require the processing of data that arrives prior to query submission or during a period of disconnection. For
Sirish Chandrasekaran +1 more
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Proceedings 41st Annual Symposium on Foundations of Computer Science, 2002
We study clustering under the data stream model of computation where: given a sequence of points, the objective is to maintain a consistently good clustering of the sequence observed so far, using a small amount of memory and time. The data stream model is relevant to new classes of applications involving massive data sets, such as Web click stream ...
S. Guha +3 more
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We study clustering under the data stream model of computation where: given a sequence of points, the objective is to maintain a consistently good clustering of the sequence observed so far, using a small amount of memory and time. The data stream model is relevant to new classes of applications involving massive data sets, such as Web click stream ...
S. Guha +3 more
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Selective ensemble-based online adaptive deep neural networks for streaming data with concept drift
Neural Networks, 2021Husheng Guo, Shuai Zhang, Wenjian Wang
semanticscholar +1 more source
2016 International Conference on Recent Trends in Information Technology (ICRTIT), 2016
In the evolving technology of big data, high velocity data streams play a vital role since pattern of data is being changed over time. The temporal pattern change in data stream leads to a concept evolution called concept drift where statistical properties of data differs from time to time and the drift is taken into account in order to update old and ...
P. V Srilakshmi Annapoorna +1 more
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In the evolving technology of big data, high velocity data streams play a vital role since pattern of data is being changed over time. The temporal pattern change in data stream leads to a concept evolution called concept drift where statistical properties of data differs from time to time and the drift is taken into account in order to update old and ...
P. V Srilakshmi Annapoorna +1 more
openaire +1 more source