Results 21 to 30 of about 3,318,937 (295)
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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Finding frequent trajectories by clustering and sequential pattern mining
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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Mining Negative Sequential Patterns with Periodic Gap Constraints [PDF]
Sequential pattern mining with gap constraints is a special form of sequential pattern mining,which can reveal frequent subsequences in a certain gap.However,the current sequential pattern mining methods with gap constraints only focus on positive ...
WANG Zhulin, WU Youxi, WANG Yuehua, LIU Jingyu
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Fault Tolerant Frequent Pattern Mining [PDF]
FP-Growth algorithm is a Frequent Pattern Min- ing (FPM) algorithm that has been extensively used to study correlations and patterns in large scale datasets. While several researchers have designed distributed memory FP-Growth algorithms, it is pivotal to consider fault tolerant FP-Growth, which can address the increasing fault rates in large scale ...
Sameh Shohdy +2 more
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Unsupervised Frequent Pattern Mining for CEP
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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A Survey of Correlated High Utility Pattern Mining
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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A Reconfigurable Platform for Frequent Pattern Mining [PDF]
In this paper, a new hardware architecture for frequent pattern mining based on a systolic tree structure is proposed. The goal of this architecture is to mimic the internal memory layout of the original FP-growth algorithm while achieving a much higher throughput.
Song Sun +2 more
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Recursive Queried Frequent Patterns Algorithm: Determining Frequent Pattern Sets from Database
Frequent 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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FP-GraphMiner-A Fast Frequent Pattern Mining Algorithm for Network Graphs
In recent years, graph representations have been used extensively for modelling complicated structural information, such as circuits, images, molecular structures, biological networks, weblogs, XML documents and so on.
R. Vijayalakshmi +4 more
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Theoretical Properties of Closed Frequent Itemsets in Frequent Pattern Mining
Closed 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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