Search Results - (( pattern ((using algorithm) OR (mining algorithm)) ) OR ( deep learning algorithms ))
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…Therefore, the present study aims: (1) to improve Indonesian text summary by enhancing the Sequence of Word (SoW) as text representation using Sequential Pattern Mining (SPM) with PrefixSpan algorithm since the effectiveness of SPM in Indonesian is proven useful for text classification and clustering; (2) to combine SPM and Deep Learning (DeepSPM) in text summarization with Indonesian text, as a result of its superior accuracy when trained with large amounts of data; and (3) to evaluate the readability of Indonesian text summary with several evaluation scenarios. …”
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A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications
Published 2022“…Without human input, these algorithms discover patterns or groupings in the data. …”
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm
Published 2023“…Automation; Complex networks; Computational complexity; Deep learning; Image analysis; Medical imaging; Pattern matching; Pixels; Distribution pattern-matching rule; Distribution patterns; Gray wolf-optimized deep convolution network; Gray wolves; Learning patterns; Matching rules; Medical fields; Medical image analysis; Pattern matching algorithms; Pattern-matching; Convolution…”
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Modifying iEclat algorithm for infrequent patterns mining
Published 2018“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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Modifying iEclat algo ithm for infrequent patterns mining
Published 2018“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The mined frequent patterns are then used in generating association rules. …”
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Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset
Published 2018“…Pattern mining refers to a subfield of data mining that uncovers interesting, unexpected, and useful patterns from transaction databases. …”
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Efficient prime-based method for interactive mining of frequent patterns.
Published 2011“…During the mining process, the mining algorithm reduces the number of candidate patterns and comparisons by using a new candidate set called candidate head set and several efficient pruning techniques. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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A Data Mining Approach to Enhancing Birth and Death Registration Processes
Published 2025“…Using k-means clustering, apriori association rules, and c5 decision trees, this research identifies key patterns influencing late registrations. …”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks
Published 2022“…Prairie Grass experiment database is used as a data to develop toxic gas dispersion prediction model based on deep learning networks. Thus, in this study, development of deep neural network is carried out using MATLAB. …”
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Prime-based method for interactive mining of frequent patterns
Published 2010“…Since rerunning the mining algorithms from scratch can be very time consuming, researchers have introduced interactive mining to find proper patterns by using the current mining model with various minsup. …”
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14
A numerical method for frequent pattern mining
Published 2009“…Frequent pattern mining is one of the active research themes in data mining. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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Expectation maximization clustering algorithm for user modeling in web usage mining system
Published 2009“…The results also indicate that kind of behavior given by EM clustering algorithm has improved the visit-coherence (accuracy) of navigation pattern mining.…”
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Deep learning in face recognition for attendance system: an exploratory study / Mochamad Azkal Azkiya Aziz, Shahrinaz Ismail and Noormadinah Allias
Published 2022“…The use of deep learning can reach 98 percent accuracy. …”
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