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An evaluation of data stream clustering algorithms
Statistical analysis and data mining, 2018Data stream clustering is a hot research area due to the abundance of data streams collected nowadays and the need for understanding and acting upon such sort of data. Unsupervised learning (clustering) comprises one of the most popular data mining tasks
Stratos Mansalis +3 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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A Study of Apache Kafka in Big Data Stream Processing
2018 International Conference on Information , Communication, Engineering and Technology (ICICET), 2018Big data the name implies huge volume of data. Now a days streaming of data is more popular model which enables real time streaming data for data analytics.
Bhole Rahul Hiraman +2 more
semanticscholar +1 more source
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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Data stream classification with novel class detection: a review, comparison and challenges
Knowledge and Information Systems, 2021Salah Ud Din +6 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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