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A Text Mining Algorithm Optimising the Determination of Relevant Studies by Khashfeh M., Mahmoud M.A., Ahmad M.S.

Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

“…The scale-up experiment showed that the proposed algorithm is more scalable than the other existing algorithms. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Improved normalization and standardization techniques for higher purity in K-means clustering by Dalatu, Paul Inuwa, Fitrianto, Anwar, Mustapha, Aida

“…Clustering is an unsupervised classification method with aim of partitioning, where objects in the same cluster are similar, and objects belong to different clusters vary significantly, with respect to their attributes. The K-means algorithm is a famous and fast technique in non-hierarchical cluster algorithms. …”
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Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

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Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

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Effective mining on large databases for intrusion detection by Adinehnia, Reza, Udzir, Nur Izura, Affendey, Lilly Suriani, Ishak, Iskandar, Mohd Hanapi, Zurina

“…Data mining is a common automated way of generating normal patterns for intrusion detection systems. …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

“…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. …”
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Concept Based Lattice Mining (CBLM) using Formal Concept Analysis (FCA) for text mining by Mumtazimah, Mohamad, Hassan, H., Mohd Saman, M.Y, Abdullah, Z.

“…The focus of this study is on the method of Concept Based Lattice Mining (CBLM) where similarities among output lattices will be compared using their normalized adjacency matrices, utilizing a distance measure technique. …”
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis by Ong, Phaik Ling

“…However, frequent pattern mining (FPM) using Apriori-like algorithms and support-confidence framework suffers from the myth of rare item problem in nature. …”
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Prediction Of Leaf Mechanical Properties Based On Geometry Features With Data Mining by H’ng, Choo Wooi

“…Findings showed that the numerical predictions on FT and ST (RRSE ~ 25%) were about two folds better than the WT and SWT (RRSE ~50%) in the six algorithms tested. The best prediction performance was gained on FT indicator using the M5P algorithm (RRSE = 22.44%). …”
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SUDOKU HELPER by Abdul Razak, Muhammad Asyraf

“…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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New approaches to normalization techniques to enhance k-means clustering algorithm by Dalatu, Paul Inuwa, Midi, Habshah

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Concept Based Lattice Mining (CLBM) Using Formal Concept Analysis (FCA) for Text Mining by Hasni, Hassan, Mumtazimah, Mohamad, Md Yazid, Mohamad Saman

“…The focus of this study is on the method of Concept Based Lattice Mining (CBLM) where similarities among output lattices will be compared using their normalized adjacency matrices, utilizing a distance measure technique. …”
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An initial state of design and development of intelligent knowledge discovery system for stock exchange database by Che Mat @ Mohd Shukor, Zamzarina, Khokhar, Rashid Hafeez, Md Sap, Mohd Noor

“…We divide our problem in two modules.In first module we define Fuzzy Rule Base System to determined vague information in stock exchange databases.After normalizing massive amount of data we will apply our proposed approach, Mining Frequent Patterns with Neural Networks.Future prediction (e.g., political condition, corporation factors, macro economy factors, and psychological factors of investors) perform an important rule in Stock Exchange, so in our prediction model we will be able to predict results more precisely.In second module we will generate clustering algorithm. …”
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Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining by Termedi @ Termiji, Mohammad Izzuan

“…CRISP is a cross-industry standard data mining process which consists of six stages of the normal lifecycle of a CRISP-DM project. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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Data mining in mobile ECG based biometric identification by Sidek, Khairul Azami, Mai, Vu, Khalil, Ibrahim

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An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs by Sadiq, Ali Safaa, Alkazemi, Basem, Mirjalili, Seyedali, Ahmed, Noraziah, Khan, Suleman, Ali, Ihsan, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

“…Experimental results show that using our proposed IDS based on hybrid MOA-PSO technique provides more accuracy level compared to the use of ANN based on MOA, PSO and genetic algorithm. Updated KDD CUP data set is formed and used during the training and testing phases, where this data set consists of mixed data traffics between attacks and normal activities. …”
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs by Sadiq, Ali Safa, Alkazemi, Basem Y., Mirjalili, Seyedali, Noraziah, Ahmad, Khan, Suleman, Ihsan, Ali, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

“…Experimental results show that using our proposed IDS based on hybrid MOA-PSO technique provides more accuracy level compared to the use of ANN based on MOA, PSO and genetic algorithm. Updated KDD CUP data set is formed and used during the training and testing phases, where this data set consists of mixed data traffics between attacks and normal activities. …”
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