Results 31 to 40 of about 24,371,806 (309)
Value Stream Mapping and Process Mining: A Lean Method Supported by Data Analytics
Proceedings of the Conference on Production Systems and Logistics, 2020 The analysis and further the reorganization of an order-production is a typical scope of application of a value stream mapping. Value stream mapping is a lean-management method to map the current state of a series of processes that are necessary to ...
Mertens, Katharina +2 more
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Deterministic, Fast and Accurate Solution of the Heavy Hitters
IEEE Access, 2022 The heavy hitters $q$ -tail latencies problem has been introduced recently. This problem, framed in the context of data stream monitoring, requires approximating the quantiles of the heavy hitters items of an input stream whose elements are pairs (item,
Anna Fornaio +3 more
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Evaluation of real-time traffic applications based on data stream mining
, 2022 S.83-103Traffic management today requires the analysis of a huge amount of data in real-time in order to provide current information about the traffic state or hazards to road users and traffic control authorities.
Geisler, Sandra, Quix, Christoph
core +1 more source
Autonomous Sensor Data Cleaning in Stream Mining Setting
Business Systems Research, 2018 Background: Internet of Things (IoT), earth observation and big scientific experiments are sources of extensive amounts of sensor big data today. We are faced with large amounts of data with low measurement costs.
Kenda Klemen, Mladenić Dunja
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SCLUSTREAM: AN EFFICIENT ALGORITHM FOR TRACKING CLUSTERS OVER SLIDING WINDOW IN BIG DATA STREAMING [PDF]
International Journal of Intelligent Computing and Information Sciences, 2019 Mining in data streams has been a hot research topic in the recent time. A main challenge in data stream mining lies in extracting knowledge in real time from a massive, dynamic data stream in only a single scan.
doaa sayed, Sherine rady, M Aref
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Towards Mining Trapezoidal Data Streams [PDF]
2015 IEEE International Conference on Data Mining, 2015 We study a new problem of learning from doubly-streaming data where both data volume and feature space increase over time. We refer to the problem as mining trapezoidal data streams. The problem is challenging because both data volume and feature space are increasing, to which existing online learning, online feature selection and streaming feature ...
Qin Zhang 0011 +5 more
openaire +1 more source
Journal of Electrical and Computer Engineering, 2020 Data stream mining has become a research hotspot in data mining and has attracted the attention of many scholars. However, the traditional data stream mining technology still has some problems to be solved in dealing with concept drift and concept ...
Xiangjun Li +4 more
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A New Algorithm of Mining High Utility Sequential Pattern in Streaming Data
International Journal of Computational Intelligence Systems, 2019 High utility sequential pattern (HUSP) mining has emerged as a novel topic in data mining, its computational complexity increases compared to frequent sequences mining and high utility itemsets mining.
Huijun Tang, Yangguang Liu, Le Wang
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Research on detection and integration classification based on concept drift of data stream
EURASIP Journal on Wireless Communications and Networking, 2019 As a new type of data, data stream has the characteristics of massive, high-speed, orderly, and continuous and is widely distributed in sensor networks, mobile communication, financial transactions, network traffic analysis, and other fields.
Baoju Zhang, Yidi Chen
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Advanced Functional Materials, EarlyView.This perspective presents recent advances in electrocatalytic nitrate reduction, focusing on reaction mechanisms, catalyst design, and electrolyzer configurations. Key challenges in selectivity, stability, and practical wastewater treatment are highlighted, while future directions for advancing sustainable ammonia synthesis and nitrate remediation are ...
Xintong Li +9 more
wiley +1 more source