Results 51 to 60 of about 26,646,267 (236)
Variability in Data Streams [PDF]
Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems, 2016 We consider the problem of tracking with small relative error an integer function $f(n)$ defined by a distributed update stream $f'(n)$. Existing streaming algorithms with worst-case guarantees for this problem assume $f(n)$ to be monotone; there are very large lower bounds on the space requirements for summarizing a distributed non-monotonic stream ...
Felber, David, Ostrovsky, Rafail
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Evaluation methods and decision theory for classification of streaming data with temporal dependence [PDF]
, 2014 Predictive modeling on data streams plays an important role in modern data analysis, where data arrives continuously and needs to be mined in real time.
Bifet, Albert +4 more
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HiSem-RAG: A Hierarchical Semantic-Driven Retrieval-Augmented Generation Method
Applied SciencesTraditional retrieval-augmented generation (RAG) methods struggle with hierarchical documents, often causing semantic fragmentation, structural loss, and inefficient retrieval due to fixed strategies.
Dongju Yang, Junming Wang
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Statistical data reduction for streaming data [PDF]
2017 New York Scientific Data Summit (NYSDS), 2017 Bulk of the streaming data from scientific simulations and experiments consists of numerical values, and these values often change in unpredictable ways over a short time horizon. Such data values are known to be hard to compress, however, much of the random fluctuation is not essential to the scientific application and could therefore be removed ...
Wu, Kesheng +3 more
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Extension of Decision Tree Algorithm for Stream Data Mining Using Real Data [PDF]
, 2009 Recently, because of increasing amount of data in the society, data stream mining targeting large scale data has attracted attention. The data mining is a technology of discovery new knowledge and patterns from the massive amounts of data, and what the ...
Ise, Masayuki +3 more
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Saber: window-based hybrid stream processing for heterogeneous architectures [PDF]
, 2015 Modern servers have become heterogeneous, often combining multicore CPUs with many-core GPGPUs. Such heterogeneous architectures have the potential to improve the performance of data-intensive stream processing applications, but they are not supported by
Costa, P +5 more
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Algorithms, 2020 Toward strong demand for very high-speed I/O for processors, physical performance growth of hardware I/O speed was drastically increased in this decade. However, the recent Big Data applications still demand the larger I/O bandwidth and the lower latency
Shinichi Yamagiwa +2 more
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A Systematic Review of Density Grid-Based Clustering for Data Streams
IEEE Access, 2022 Various applications, such as electronic business, satellite remote sensing, intrusion discovery, and network traffic monitoring, generate large unbounded data stream sequences at a rapid pace.
Mustafa Tareq +3 more
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, 2012 Data stream management systems (DSMS) so far focus on event queries and hardly consider combined queries to both data from event streams and from a database.
Brodt, Simon, Bry, François
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AutomationThe paper puts forth a methodology for the arrangement of calculation control at the outputs of combinational digital devices based on utilizing multiple diagnostic features.
Dmitry V. Efanov +4 more
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