Results 21 to 30 of about 23,652 (302)
KIPS Transactions on Software and Data Engineering, 2016 현존하는 빈발 패턴 마이닝 방법은 대부분 시간 효율성을 목표로 하고, 물리적 메모리 사용에 매우 의존적이다. 하지만 빅데이터 시대가 도래함에 따라 실제 세상의 데이터베이스는 급속도로 증가하고 있으며, 그에 따라 기존의 방법으로 현실적인 거대한 양의 데이터를 마이닝하기에 물리적 메모리 공간이 부족한 실정이다. 이러한 문제를 해결하기 위해, 빈발 패턴 마이닝의 메모리 의존성을 줄이기 위한 보조저장장치 기반의 연구들이 진행되었으나, 메모리 기반의 방법들에 비해 처리 시간이 너무 많이 소비된다는 한계가 있었다.
Jung-Hun Lee, Youn-A Min
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International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2020 Frequent pattern mining has been an important subject matter in data mining from many years. A remarkable progress in this field has been made and lots of efficient algorithms have been designed to search frequent patterns in a transactional database. One of the most important technique of datamining is the extraction rule in large database.
Y. Fakir, R. Elayachi
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Mining Frequent Patterns in Evolving Graphs
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018 Given a labeled graph, the frequent-subgraph mining (FSM) problem asks to find all the $k$-vertex subgraphs that appear with frequency greater than a given threshold. FSM has numerous applications ranging from biology to network science, as it provides a compact summary of the characteristics of the graph. However, the task is challenging, even more so
Nasir, Muhammad Anis Uddin +4 more
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Unsupervised Frequent Pattern Mining for CEP
CoRR, 2022 Complex Event Processing (CEP) is a set of methods that allow efficient knowledge extraction from massive data streams using complex and highly descriptive patterns. Numerous applications, such as online finance, healthcare monitoring and fraud detection use CEP technologies to capture critical alerts, potential threats, or vital notifications in real ...
Guy Shapira, Assaf Schuster
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Finding frequent trajectories by clustering and sequential pattern mining
Journal of Traffic and Transportation Engineering (English ed. Online), 2014 Data mining is a powerful emerging technology that helps to extract hidden information from a huge volume of historical data. This paper is concerned with finding the frequent trajectories of moving objects in spatio-temporal data by a novel method ...
Arthur A. Shaw, N.P. Gopalan
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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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Mining Frequent Seasonal Gradual Patterns [PDF]
, 2020 Gradual patterns that capture co-variation of complex attributes in the form “when X increases/decreases, Y increases/decreases” play an important role in many real world applications where huge volumes of complex numerical data must be handled. More recently, they have received attention from the data mining community for exploring temporal data and ...
Jerry Lonlac +3 more
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Recursive Queried Frequent Patterns Algorithm: Determining Frequent Pattern Sets from Database
InformationFrequent pattern mining is a fundamental method for Data Mining, applicable in market basket analysis, recommendation systems, and academic analytics. Widely adopted and foundational algorithms such as Apriori and FP-Growth, which represent the standard ...
Ishtiyaq Ahmad Khan +3 more
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MISFP-Growth: Hadoop-Based Frequent Pattern Mining with Multiple Item Support
Applied Sciences, 2019 In practice, single item support cannot comprehensively address the complexity of items in large datasets. In this study, we propose a big data analytics framework (named Multiple Item Support Frequent Patterns, MISFP-growth algorithm) that uses Hadoop ...
Chen-Shu Wang, Jui-Yen Chang
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Mining association rules for the quality improvement of the production process [PDF]
, 2013 Academics and practitioners have a common interest in the continuing development of methods and computer applications that support or perform knowledge-intensive engineering tasks.
Rigal, Fabien +2 more
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