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53 articles for “Unsupervised”
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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 titleCharacterization of the Earth's Surface State by Unsupervised Classification: Case of Vegetated, Aquatic and Mineral SurfacesJean-Claude Okaingni, Sié Ouattara, Adles Kouassi, Alain ClémentIn this study, we propose an unsupervised classification scheme based on the Dempster-Shafer Theory (TDS) and the Dezert-Smarandache Theory (DSmT) to characterize vegetated, aquatic and mineral surfaces. From pre-processed ASTER satellite images (georeferencing, geometric correction and 15 m re-sampling), neo-channels were produced by determining the spectral indices NDVI, MNDWI and NDBaI, considered as sources of information for classification of a … …American Journal of Applied Sciences, Vol. 15, Issue 7 · 27 Aug 2018 · 8,176 accessesView PDFCite
Research ArticleOpen accessEvery word 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 titleA Misuse and Anomaly Intrusion Detection System Using Hybrid Supervised and Unsupervised Data Mining ApproachesHoma Molavi, Mohammad KhanbabaeiIntrusion Detection Systems (IDSs) play a crucial role in monitoring computer network security. Data mining and machine learning techniques facilitate the identification of intrusion patterns within large volumes of data. Hybrid data mining models have become increasingly popular in IDSs due to their enhanced effectiveness. This study presents a novel hybrid IDS that combines misuse and anomaly detection by integrating … …Journal of Computer Science, Vol. 22, Issue 6 · 6 Jul 2026 · 999 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleUnsupervised Cosegmentation Model based on Saliency Detection and Optimized Hue Saturation Value Features of SuperpixelsRasha Shoitan, Mona M. MoussaSegmenting out the foreground from a single image remains a challenge in computer vision. Image co-segmentation has been used recently to alleviate the single image segmentation by exploiting the information of the common object to be segmented from a group of images having the same object. This research proposes an unsupervised co-segmentation technique based on saliency detection and optimized features … …Journal of Computer Science, Vol. 17, Issue 7 · 3 Aug 2021 · 7,003 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Comparative Study in Classification Techniques for Unsupervised Record Linkage ModelMohammadreza Ektefa, Fatimah Sidi, Hamidah Ibrahim et al.Problem statement: Record linkage is a technique which is used to detect and match duplicate records which are generated in data integration process. A variety of record linkage algorithms with different steps have been developed in order to detect such duplicate records. To find out whether two records are duplicate or not, supervised and unsupervised classification techniques are utilized in … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 8,199 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