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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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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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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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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
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Clustering Multiple Data Streams
2011In recent years, data streams analysis has gained a lot of attention due to the growth of applicative fields generating huge amount of temporal data. In this paper we will focus on the clustering of multiple streams. We propose a new strategy which aims at grouping similar streams and, together, at computing summaries of the incoming data.
BALZANELLA, Antonio +2 more
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Data Streams Processing Techniques Data Streams Processing Techniques
2017Many modern applications in several domains such as sensor networks, financial applications, web logs and click-streams operate on continuous, unbounded, rapid, time-varying streams of data elements. These applications present new challenges that are not addressed by traditional data management techniques.
Fatma Mohamed +3 more
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2014
It is possible today to collect streams of data from sensors in the environment (e.g., on walls of buildings) or attached to individuals (e.g., badges that record location and with whom one is speaking). The data from these sensors allows researchers to trace people’s behavior with and without various technology interventions or incentives intended to ...
Stephen Voida +2 more
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It is possible today to collect streams of data from sensors in the environment (e.g., on walls of buildings) or attached to individuals (e.g., badges that record location and with whom one is speaking). The data from these sensors allows researchers to trace people’s behavior with and without various technology interventions or incentives intended to ...
Stephen Voida +2 more
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Data Streams and Data Stream Management Systems and Languages
2015The massive usage of data streams dates back to artificial satellite information processing systems and to their commercial application in the early 1970s, such as in telecommunications switching, land monitoring, meteorological surveillance, etc. Today they are extensively used in monitoring systems applications based on wired and wireless sensor ...
PANIGATI, EMANUELE +2 more
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