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Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

“…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 by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

“…On the other hand, the offline phase is evoked when the user requests to view the overall clustering results. The DBSCAN algorithm is used to perform the macro clustering task by replacing the distance between trajectories segments with the distance between the temporal micro-clusters. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…The reliable relationship between EEG signals of the attention and meditation and their impact towards the positive and negative emotions among children while learning illustrates the potentials in detecting mental states which are relevant to tutoring such as comprehension, engagement and learning impact. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…In order to investigate the correlation between features and class, generated feature subsets are rearranged according to its mutual information. …”
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Detection on ambiguous software requirements specification written in malay using machine learning by Zahrin, Mohd Firdaus

“…Unfortunately, the structure of writing between Malay and English is totally different. Hence, we propose a framework to detect ambiguity on SRS using supervised machine learning technique. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…This research opens a wide range of future work to be considered, which includes applying the proposed method in other areas such as web mining, text mining or multimedia mining; and extending the proposed approach to work in parallel computing in data mining.…”
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A modified π rough k-means algorithm for web page recommendation system by Zidane, Khaled Ali Othman

“…The experimental results revealed that the modified πRKM algorithm performed better than the previous version in terms of the correct identification of overlapping objects between positive clusters. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

“…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

“…The existing approaches are based on traditional machine learning algorithms, such as support vector machine (SVM). …”
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A prototype for context identification of scientific papers via agent-based text mining by Mahmoud M.A., Ahmad M.S.

An automated learner for extracting new ontology relations by Amaal Saleh Hassan, Al Hashimy, Narayanan, Kulathuramaiyer

“…Also we present a novel approach of learning based on the best lexical patterns extracted, besides two new algorithms the CIA and PS that provide the final set of rules for mining causation to enrich ontologies.…”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The experimental results demonstrate that the proposed algorithm is competitive compared to the state-of-the-art semi-supervised learning algorithms in terms of accuracy. …”
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A comprehensive analysis of blockchain-based cryptocurrency mining impact on energy consumption by Islam, Md Rafiqul, Rashid, Muhammad Mahbubur, Rahman, Mohammed Ataur, Mohamad, Muslim Har Sani, Embong, Abd Halim

“…The Proof-of-Work (PoW) algorithm is used for mining ‘Bitcoin’ which is consumed enormous computational power. …”
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Mining dense data: Association rule discovery on benchmark case study by Bakar, W.A.W.A., Saman, M.D.M., Abdullah, Z., Jalil, M.A., Herawan, T.

“…In this article, we present comparison result between Apriori and FP-Growth algorithm in generating association rules based on a benchmark data from frequent itemset mining data repository. …”
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Prediction of ADHD from a small dataset using an adaptive EEG theta/beta ratio and PCA feature extraction by Sase, Takumi, Othman, Marini

“…Due to the heterogeneity of ADHD symptoms, several studies have applied machine learning algorithms for enhancing the recognition of ADHD. …”
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Dissimilarity algorithm on conceptual graphs to mine text outliers by Kamaruddin, Siti Sakira, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Mat Nor, Fauzias

“…The graphical text representation method such as Conceptual Graphs (CGs) attempts to capture the structure and semantics of documents.As such, they are the preferred text representation approach for a wide range of problems namely in natural language processing, information retrieval and text mining.In a number of these applications, it is necessary to measure the dissimilarity (or similarity) between knowledge represented in the CGs.In this paper, we would like to present a dissimilarity algorithm to detect outliers from a collection of text represented with Conceptual Graph Interchange Format (CGIF).In order to avoid the NP-complete problem of graph matching algorithm, we introduce the use of a standard CG in the dissimilarity computation.We evaluate our method in the context of analyzing real world financial statements for identifying outlying performance indicators.For evaluation purposes, we compare the proposed dissimilarity function with a dice-coefficient similarity function used in a related previous work.Experimental results indicate that our method outperforms the existing method and correlates better to human judgements. …”
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An application of predicting student performance using kernel k-means and smooth support vector machine by Sajadin, Sembiring

“…In this study, psychometric factors used as predictor variables, thereare Interest, Study Behavior, Engaged Time, Believe, and Family Support.The rulemodel developed using Kernel K-means Clustering and Smooth Support Vector MachineClassification.Both of these techniquesbased on kernel methodsand relativelynew algorithms of data mining techniques, recently received increasingly popularity in machine learning community. …”
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