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38 articles for “Unsupervised Learning”
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Research ArticleOpen accessPhrase in the titleVIRTUAL MINING MODEL FOR CLASSIFYING TEXT USING UNSUPERVISED LEARNINGS. Koteeswaran, E. Kannan, P. VisuIn real world data mining is emerging in various era, one of its most outstanding performance is held in various research such as Big data, multimedia mining, text mining etc. Each of the researcher proves their contribution with tremendous improvements in their proposal by means of mathematical representation. Empowering each problem with solutions are classified into mathematical and implementation models. … …American Journal of Applied Sciences, Vol. 11, Issue 5 · 20 Feb 2014 · 6,582 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSentiment Analysis of Arabic Reviews for Saudi Hotels Using Unsupervised Machine LearningSamar Alosaimi, Maram Alharthi, Khloud Alghamdi et al.Virtual worlds such as social networking sites, blogs and content communities are extremely becoming one of the most powerful sources for news, markets, industries etc. These virtual worlds can be used for many aspects, because they are rich platforms full of feedback, emotions, thoughts and reviews. The main objective of this paper is to cluster Arabic reviews of Saudi hotels … …Journal of Computer Science, Vol. 16, Issue 9 · 25 Sep 2020 · 7,156 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification of Breast Tumor in Mammogram Images Using Unsupervised Feature LearningAidarus M. Ibrahim, Baharum Baharudin, Abas Md Said, P. N. HashimahIn this study, we propose a learning-based approach using feature learning to minimize the manual effort required to extract features. Firstly, we extracted features from equally spaced sub-patches covering the input Region of Interest (ROI). The dimensionality of the extracted features is reduced using max-pooling. Furthermore, spherical k-means clustering coupled with max pooling (k-means-max pooling) is compared with well-known feature … …American Journal of Applied Sciences, Vol. 13, Issue 5 · 13 May 2016 · 7,497 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAutoencoder-Based Intrusion Detection for ARP Poisoning in SDN ControllersKago Seemela, Banyatsang Mphago, Thabo Semong, Phephisa MethulaAddress Resolution Protocol (ARP) poisoning is still a critical control plane attack in Software Defined Networks (SDNs), and spoofing of ARP mappings can trick SDNs controller and accomplish man in the middle, eavesdropping and denial of service attacks. Current SDN intrusion detection systems of ARP attacks rely on supervised learning and labelled attack data which is rather expensive and not … …Journal of Computer Science, Vol. 22, Issue 7 · 21 Jul 2026 · 869 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSkin Images SegmentationAli El-ZaartProblem statement: Image segmentation is a fundamental step in many applications of image processing. Skin cancer has been the most common of all new cancers detected each year. At early stage detection of skin cancer, simple and economic treatment can cure it mostly. An accurate segmentation of skin images can help the diagnosis to define well the region of the … …Journal of Computer Science, Vol. 6, Issue 2 · 28 Jul 2010 · 7,023 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSpatio-Temporal Anomaly Detection in Groundwater Electrical Conductivity Using a Hybrid Framework of Isolation Forest and AutoencoderEunji Lee, Seunghyun Lim, Seojun Lee, Abhijit DebnathMonitoring groundwater quality is vital for environmental safety and resource sustainability. This study combines Isolation Forest and Autoencoder models to detect anomalies in Electrical Conductivity (EC) and temperature, using monthly data collected in South Korea between 2006 and 2023. Linear regression and the Mann-Kendall test reveal a weak, episodic downward EC trend. Seasonal decomposition indicates annual cyclicality, while residual analysis … …Journal of Computer Science, Vol. 22, Issue 1 · 14 Feb 2026 · 1,918 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Anomaly Detection Approach for Nifty Stocks using Machine Learning for Construction of Efficient Portfolio to Reduce Losses and Protect GainsVirrat Devaser, Priyanka ChawlaMachine Learning is the most essential and widely utilized methodological approach these days for performing, organizing, and analyzing data using a variety of approaches to produce correct and efficient results. Machine learning methodologies are also applicable to stock markets, which have grown multi-fold in recent years, and with the amount of money involved, the possibility of manipulation is always present … …Journal of Computer Science, Vol. 18, Issue 5 · 6 Jun 2022 · 6,443 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEvaluation of Classification Models for Predicting Mortality Rate Using Thyroid Cancer DataNorah Saleh AlghamdiMachine Learning (ML) can potentially enhance predictions in real-life domains. This study presents an evaluation and comparison of different ML methods which can be applied on thyroid cancer dataset, called Prostate, Lung, Colorectal and Ovarian (PLCO), of approximately 155,000 participants with thyroid cancer occurrence and mortality incidence. The ML models are explored for predicting mortality rates of patients with thyroid … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 7,788 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA NOVEL EMAIL RESPONSE ALGORITHM FOR EMAIL MANAGEMENT SYSTEMSAbdulkareem Al-AlwaniEmail has been one of the most commonly used tool for communication in the recent years and email management has evolved as a major challenge due to prevailing situation of online email congestion. This study presents a novel algorithm for automatic email response methodology in an Email Management System to minimize email overload. The proposed model uses Bayes classifier to … …Journal of Computer Science, Vol. 10, Issue 4 · 23 Dec 2013 · 7,049 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSelf-Organizing Map and Multi-Layer Perceptron Neural Network Based Data Mining To Envisage Agriculture CultivationE. T. Venkatesh, Dr. P. ThangarajStudy on characteristics of soil, to determine the types of crops suitable for cultivation in a particular region can increase the yield to greater extent, which minimizes the expenditures involved in irrigation and application of fertilizers. With the tested techniques available for calibrating the quality of soil and the crops suitable for cultivation in it, it is possible to determine … …Journal of Computer Science, Vol. 4, Issue 6 · 30 Jun 2008 · 6,785 accessesView PDFCite