Search Results - (( developing features mining algorithm ) OR ( java implementation level algorithm ))
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AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING
Published 2021“…The encryption algorithms are playing an important part in the protection level for data. …”
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Tree-based contrast subspace mining method
Published 2020“…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Feature selection with integrated Gaussian seahorse optimization data mining for cross-border business cooperation between the Malaysian medical industry and tourism industry
Published 2023“…The integrated GSH-DM approach showcases the potential of combining feature selection techniques with advanced optimization algorithms in data mining applications. …”
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A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi
Published 2015“…The major finding of this review is that context-specific text mining algorithms are lacking. The main underlying text-mining challenge that seems to deserve immediate attention is the sparse and high dimensional nature of the feature-space. …”
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Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images
Published 2014“…The images were used to explore the combined performance of a data mining (DM) algorithm and object-based image analysis (OBIA). …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Enhanced ontology-based text classification algorithm for structurally organized documents
Published 2015“…This research combines the ontology and text representation for classification by developing five algorithms. The first and second algorithms namely Concept Feature Vector (CFV) and Structure Feature Vector (SFV), create feature vector to represent the document. …”
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Implementation of (AES) Advanced Encryption Standard algorithm in communication application
Published 2014“…Internet communication has become more common in this modern world recently, and one of the important algorithms used is ABS algorithm. However, most of the users have inadequate knowledge and understanding regard to this algorithm implementation in the communication field, as well as the level of security and accuracy will be questioned by the users because of the necessary to maintain the confidentiality of particular data transferred. …”
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Undergraduates Project Papers -
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Prediction Of Leaf Mechanical Properties Based On Geometry Features With Data Mining
Published 2019“…The linear models and rules developed from the M5P algorithm were adopted for the FT indicator prediction modelling of 14 attributes. …”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…It does not consider the LACE algorithm implemented in huge number of server in one Cloud datacenter. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Using text mining algorithm to detect gender deception based on Malaysian chat room lingo / Dianne L. M. Cheong and Nur Atiqah Sia Abdullah @ Sia Sze Yieng
Published 2006“…Inference can be made both from writing style and from clues hidden in the posting data. A text-mining algorithm was designed to detect gender deception based on gender-preferential features at the word or clause level of Malaysian e-mail users. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…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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A simultaneous spam and phishing attack detection framework for short message service based on text mining approach
Published 2017“…These phases are done with the use of Rapidminer and the Weka data mining tool. Three (3) types of features are used in this framework, which are the Generic Features, Payload Features and Hybrid Features. …”
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15
Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks
Published 2019“…Experiment results on several multimedia applications have shown that the proposed algorithm is competitive compared with the other single-view feature selection algorithms.…”
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Using text mining algorithm to detect gender deception based on Malaysian chatroom lingo / Dianne L.M. Cheong and Nur Atiqah Sia Abdullah@Sia Sze Yieng
Published 2006“…Based on this designed text algorithm, a prototype in Visual Basic is developed. …”
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Research Reports -
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A Model for Evaluation of Cryptography Algorithm on UUM Portal
Published 2004“…Level one is the development of userID and password, level two involve the insertion of the testing parameter speed coding. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. The test results show that the Boyer Moore and Knuth Morris Pratt algorithms have an accuracy rate of 100%, and the Horspool algorithm 85.3%. …”
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Journal -
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Improved building roof type classification using correlation-based feature selection and gain ratio algorithms
Published 2017“…First, the feature importance was evaluated using gain ratio algorithm, and the result was ranked, leading to selection of the optimal feature subset. …”
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