Results 11 to 20 of about 648,662 (306)
Network Anomaly Detection by Using a Time-Decay Closed Frequent Pattern [PDF]
Information, 2019 Anomaly detection of network traffic flows is a non-trivial problem in the field of network security due to the complexity of network traffic. However, most machine learning-based detection methods focus on network anomaly detection but ignore the user ...
Ying Zhao +6 more
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Theoretical Properties of Closed Frequent Itemsets in Frequent Pattern Mining
MathematicsClosed frequent itemsets (CFIs) play a crucial role in frequent pattern mining by providing a compact and complete representation of all frequent itemsets (FIs).
Huina Zhang +4 more
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Discovering Exclusive Patterns in Frequent Sequences [PDF]
, 2010 This paper presents a new concept for pattern discovery in frequent sequences with potentially interesting applications. Based on data mining, the approach aims to discover exclusive sequential patterns (ESP) by checking the relative exclusion of ...
Weiru Chen +5 more
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ISPRS International Journal of Geo-Information, 2020 Real-word phenomena, such as ocean eddies and clouds, tend to split and merge while they are moving around within a space. Their trajectories usually bear one or more branches and are accordingly defined as complex trajectories in this study.
Huimeng Wang +4 more
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A Survey of Correlated High Utility Pattern Mining
IEEE Access, 2021 Pattern mining is an unsupervised data mining approach aims to find interesting patterns that can be used to support decision-making. High Utility Pattern Mining (HUPM) aims to extract patterns having high utility or importance which has broad ...
Rashad S. Almoqbily +2 more
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An Improving Approach for Top-Rank- Frequent Pattern Mining
Vietnam Journal of Computer Science, 2022 Mining frequent patterns (FPs) received a lot of research interest which is a fundamental problem in the field of data mining. It has been studied on many database types with various applications in intelligent systems.
Ham Nguyen
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A Survey on Behavioral Pattern Mining From Sensor Data in Internet of Things
IEEE Access, 2020 The deployment of large-scale wireless sensor networks (WSNs) for the Internet of Things (IoT) applications is increasing day-by-day, especially with the emergence of smart city services.
Md. Mamunur Rashid +4 more
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Reducing the Frequent Pattern Set [PDF]
Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006 One of the major problems in frequent pattern mining is the explosion of the number of results, making it difficult to identify the interesting frequent patterns. In a recent paper [7] we have shown that an MDL-based approach gives a dramatic reduction of the number of frequent item sets to consider.
Bathoorn, R.W. +2 more
openaire +2 more sources
Mining Human Activity Patterns From Smart Home Big Data for Health Care Applications
IEEE Access, 2017 Nowadays, there is an ever-increasing migration of people to urban areas. Health care service is one of the most challenging aspects that is greatly affected by the vast influx of people to city centers.
Abdulsalam Yassine +2 more
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Multi-step spectrum occupancy prediction method based on association rule mining
Dianzi Jishu Yingyong, 2020 Radio spectrum occupancy prediction is a key technology in cognitive radio research. In the traditional method, only single step size prediction can be performed, and the effect of multi-step size prediction is significantly reduced.
Jing Tong, Ding Wenrui, Liu Chunhui
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