Search Results - (( pattern using algorithm ) OR ( between ((mining algorithm) OR (means algorithm)) ))
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A modified π rough k-means algorithm for web page recommendation system
Published 2018“…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering
Published 2021“…In this paper, we have compared the performance of K-Mean and XMean clustering algorithms using two datasets of student enrollment in higher education institutions. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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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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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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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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11
Assessing data mining as an alternative in discovering customer consumption pattern / Abdul Malik Hafiy Mohd Jeffri, Muhammad Aqil Zulkifli and Sukri Nasruddin
Published 2019“…Data were analysed by using Rstudio software and apriori algorithm is used for obtaining the pattern. …”
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A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining
Published 2009“…The approach in the offline phase is based on the new graph partitioning algorithm to model user navigation patterns for the navigation patterns mining. …”
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An analysis of text mining factors enhancing the identification of relevant studies
Published 2023“…The second component is the search process that is operated by a pattern matching. The third process is the parsing that is operated by a text mining algorithm. …”
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Comparative study of apriori-variant algorithms
Published 2016“…One of data mining methods is frequent itemset mining that has been implemented in real world applications, such as identifying buying patterns in grocery and online customers’ behavior.Apriori is a classical algorithm in frequent itemset mining, that able to discover large number or itemset with a certain threshold value. …”
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Discovering Pattern in Medical Audiology Data with FP-Growth Algorithm
Published 2012“…We use frequent pattern growth (FP-Growth) algorithm in the data processing step to build the FP-tree data structure and mine it for frequents itemsets. …”
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Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
Published 2009“…We ¯nd between 96% and 99.7 % of accuracy in the classi¯cation of 6 di®erent types of Time series by using K-means cluster algorithm and we ¯nd 99.7% by using the new clustering algorithm.…”
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Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
Published 2008“…We ¯nd between 96% and 99.7 % of accuracy in the classi¯cation of 6 di®erent types of Time series by using K-means cluster algorithm and we ¯nd 99.7% by using the new clustering algorithm.…”
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18
Identifying Relationship between Hearing loss Symptoms and Pure-tone Audiometry Thresholds with FP-Growth Algorithm
Published 2013“…The purpose of this study was to find the relationship that exists between pure-tone audiometry threshold values and hearing loss symptoms in a medical datasets of 339 hearing loss patients using association rule mining algorithm. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques
Published 2014“…The aim for this paper is to propose a comparison study between two well-known clustering algorithms namely fuzzy c-means (FCM) and k-means. …”
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