Results 241 to 250 of about 23,720,719 (291)

Stream Operators for Querying Data Streams

2005
One of the most important uses of aggregate queries over data streams is sampling. Typically, aggregation is performed over sliding windows where queries return new results whenever the window contents change, a concept referred to as a continuous query.
Lisha Ma, Stratis Viglas, Meng Li, Qian Li   +3 more
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Data stream warehousing

2014 IEEE 30th International Conference on Data Engineering, 2013
Data stream warehousing is a data management technology designed to simultaneously handle big-data and fast-data. Conceptually, a data stream warehouse can be thought of as a data warehouse system that is updated in nearly-real time rather than during downtimes, or as a data stream management system that stores a very long history. In this tutorial, we
Lukasz Golab, Theodore Johnson
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On the monotonicity of a data stream

Combinatorica, 2014
In this paper the authors consider problems related to the sortedness of a data stream. In the first part of this work the problem of estimating the distance to monotonicity is investigated. Then the problem of approximating the length of the longest increasing subsequence of the input stream is discussed.
Funda Ergün, Hossein Jowhari
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Recommendations For Streaming Data

Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, 2016
Recommender systems have become increasingly popular in recent years because of the broader popularity of many web-enabled electronic commerce applications. However, most recommender systems today are designed in the context of an offline setting.
Karthik Subbian, Charu C. Aggarwal, Kshiteesh Hegde   +2 more
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Data-streams and histograms

Proceedings of the thirty-third annual ACM symposium on Theory of computing, 2001
Histograms have been used widely to capture data distribution, to represent the data by a small number of step functions. Dynamic programming algorithms which provide optimal construction of these histograms exist, albeit running in quadratic time and linear space.
Sudipto Guha, Nick Koudas, Kyuseok Shim
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Differencing Data Streams

9th International Database Engineering & Application Symposium (IDEAS'05), 2006
We present external-memory algorithms for differencing large hierarchical datasets. Our methods are especially suited to streaming data with bounded differences. For input sizes m and n and maximum output (difference) size e, the I/O, RAM, and CPU costs of our algorithm rdiff are, respectively, m + n, 4e + 8, and O(MN).
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General data streaming

Proceedings 19th IEEE Real-Time Systems Symposium (Cat. No.98CB36279), 2002
This work presents a new I/O system design and implementation targeted at applications that perform data streaming. The approach yields true zero-copy transfers between I/O devices in many instances. We give a general characterization of I/O elements and provide a framework that allows analysis of the potential for zero-copy transfers.
Frank W. Miller, Peter J. Keleher, Satish K. Tripathi   +2 more
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Data Stream Sharing

2006
Recent research efforts in the fields of data stream processing and data stream management systems (DSMSs) show the increasing importance of processing data streams, e. g., in the e-science domain. Together with the advent of peer-to-peer (P2P) networks and grid computing, this leads to the necessity of developing new techniques for distributing and ...
Richard Kuntschke, Alfons Kemper
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Warping the time on data streams

Data & Knowledge Engineering, 2007
Continuously monitoring through time the correlation/distance of multiple data streams is of interest in a variety of applications, including financial analysis, video surveillance, and mining of biological data. However, distance measures commonly adopted for comparing time series, such as Euclidean and Dynamic Time Warping (DTW), either are known to ...
CAPITANI, PAOLO, CIACCIA, PAOLO
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Data streaming 2.0

Communications of the ACM, 2010
In today's real-time Web, data streaming applications no longer have the luxury of making multiple passes over a recorded data set.
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