Realization of Resource Service Based on Web Data Stream Mining
Gong-kuang zidonghua, 2010 In order to improve utilization rate and optimize website, the paper established a Web data stream mining system and introduced the system's frame structure.
WANG Chun-xia
doaj
Data Stream Clustering Techniques, Applications, and Models: Comparative Analysis and Discussion
Big Data and Cognitive Computing, 2018 Data growth in today’s world is exponential, many applications generate huge amount of data streams at very high speed such as smart grids, sensor networks, video surveillance, financial systems, medical science data, web click streams, network ...
Umesh Kokate +3 more
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Identifying Correlated Heavy-Hitters in a Two-Dimensional Data Stream [PDF]
, 2013 We consider online mining of correlated heavy-hitters from a data stream. Given a stream of two-dimensional data, a correlated aggregate query first extracts a substream by applying a predicate along a primary dimension, and then computes an aggregate ...
Lahiri, Bibudh +2 more
core
MIDAS: Open-source framework for distributed online analysis of data streams
SoftwareX, 2018 Data streams are pervasive but implementing online analysis of streaming data is often nontrivial as data streams can have different, domain-specific formats.
Andreas Henelius, Jari Torniainen
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An efficient closed frequent itemset miner for the MOA stream mining system [PDF]
, 2013 Mining itemsets is a central task in data mining, both in the batch and the streaming paradigms. While robust, efficient, and well-tested implementations exist for batch mining, hardly any publicly available equivalent exists for the streaming scenario ...
Bifet Figuerol, Albert Carles +2 more
core +1 more source
Towards online concept drift detection with feature selection for data stream classification [PDF]
, 2016 Data Streams are unbounded, sequential data instances that are generated very rapidly. The storage, querying and mining of such rapid flows of data is computationally very challenging.
Hammoodi, Mahmood +2 more
core
Adversarial concept drift detection under poisoning attacks for robust data stream mining. [PDF]
Mach Learn, 2022 Korycki Ł, Krawczyk B.
europepmc +1 more source
The ABACOC Algorithm: a Novel Approach for Nonparametric Classification of Data Streams
, 2015 Stream mining poses unique challenges to machine learning: predictive models are required to be scalable, incrementally trainable, must remain bounded in size (even when the data stream is arbitrarily long), and be nonparametric in order to achieve high ...
Cesa-Bianchi, Nicolò +2 more
core +1 more source
Research on wireless distributed financial risk data stream mining based on dual privacy protection
EURASIP Journal on Wireless Communications and Networking, 2020 With the advancement of network technology and large-scale computing, distributed data streams have been widely used in the application of financial risk analysis.
Yuhao Zhao
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Adaptive Mining Techniques for Data Streams Using Algorithm Output Granularity Mohamed [PDF]
, 2003 Mining data streams is an emerging area of research given the potentially large number of business and scientific applications. A significant challenge in analyzing /mining data streams is the high data rate of the stream.
Arkady Zaslavsky +2 more
core +1 more source