Search Results - (( using selection method algorithm ) OR ( sequence classification mining algorithm ))

Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining by Dian Sa’adillah Maylawati

“…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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Data Mining for Building Neural Protein Sequence Classification Systems with Improved Performance by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

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Data mining of protein sequences with amino acid position-based feature encoding technique by Iqbal, M.J., Faye, I., Md Said, A., Samir, B.B.

“…The classification results indicate that the proposed encoding technique with a decision tree classification algorithm has achieved 85.9 classification accuracy over the Yeast protein sequence dataset. …”
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Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

“…In this paper, a systematic way to evaluate the association rules discovered from frequent itemset mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriated sequence of usage is presented. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer by Bashar M. A., Tahayna

“…Sentiment analysis algorithms used to classify the sentiment of tweets on social media platforms such as Twitter face challenges when dealing with idiomatic expressions and figurative language used by users. …”
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Improved GART neural network model for pattern classification and rule extraction with application to power systems by Yap K.S., Lim C.P., Au M.T.

A review on data stream classification by A. A, Haneen, A., Noraziah, Abd Wahab, Mohd Helmy

“…As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.…”
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A Review on Data Stream Classification by A. A., Haneen, Noraziah, Ahmad, Mohd Helmy, Abd Wahab

“…As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.…”
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Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

“…Polarity classification or sentiment analysis is considered one of the opinion mining tasks which distinguishes between the polarities categories (two, three, and five) of opinions which focus on the degree of the sentiment (such as positive and negative for two polarities; and positive, neutral and negative for three polarities) that the text may contain. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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Comparison for selection technique in genetic algorithm by Muhamad Azree, Mat Said

“…The purpose of this project is to make a comparison for three selection techniques in Genetic Algorithm.The Genetic Algorithm has been implemented in the previous module for Chess Tournament Management System.Base on previous system the selection method only using randomize.By this project module,only three selections method were use for the comparison.They are Roulette Wheel, Steady-State and Rank selection.The result for this comparison has determined the appropriate selection for Genetic Algorithm implementation in Chess Tournament Management System.This will help Chess Tournament Management System to provide a better optimize schedule.…”
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A decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for bachelor in multimedia / Asmaa Musa by Musa, Asmaa

“…A key stage in the system process is the selection of features. This paper discuss about a decision support system using Neurofuzzy algorithm methods in selecting lecturer's teaching work load for Bachelor in Multimedia. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…Results of the reviewed techniques show that attribute selection methods capable to resolve the limitations in ID3 algorithm and increase the performance of the method. …”
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Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…The classification of this type of dataset requires Feature Selection (FS) methods for the extraction of useful information. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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Enhanced selection method for genetic algorithm to solve traveling salesman problem by Jubeir, Mohammed, Almazrooie, Mishal, Abdullah, Rosni

“…Stochastic Universal Selection (SUS) is one of the selection methods in GA which is considered fast but it leads to lower quality solution.Although using Rank Method Selection (RMS) may lead to high quality solution, it has long runtime.In this work, an enhanced selection method is presented which maintains both fast runtime and high solution quality.First, we present a framework to solve TSP using GA with the original selection method SUS. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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