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104 results for “Features selection”

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Research ArticleOpen accessAll words, across the recordEfficacious Geospatial Information Retrieval Using Density Probabilistic Document Correlation ApproachR. Uma, MuneeswaranInformation Retrieval (IR) is a profound technique to find information that addresses the need of query. Processing of normal text is easier and information can be retrieved efficiently. There are plenty of algorithms in hand to carry out the normal text retrieval. Whereas retrieving geospatial information is very complex and requires additional operations to be performed. Since geospatial data contain … …Journal of Computer Science, Vol. 9, Issue 1 · 16 Feb 2013 · 7,011 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordNovel Moment Features Extraction for Recognizing Handwritten Arabic LettersGheith Abandah, Nasser AnssariProblem statement: Offline recognition of handwritten Arabic text awaits accurate recognition solutions. Most of the Arabic letters have secondary components that are important in recognizing these letters. However these components have large writing variations. We targeted enhancing the feature extraction stage in recognizing handwritten Arabic text. Approach: In this study, we proposed a novel feature extraction approach of handwritten Arabic … …Journal of Computer Science, Vol. 5, Issue 3 · 31 Mar 2009 · 7,495 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordHYPERPARAMETER SELECTION IN KERNEL PRINCIPAL COMPONENT ANALYSISMd. Ashad Alam, Kenji FukumizuIn kernel methods, choosing a suitable kernel is indispensable for favorable results. No well-founded methods, however, have been established in general for unsupervised learning. We focus on kernel Principal Component Analysis (kernel PCA), which is a nonlinear extension of principal component analysis and has been used electively for extracting nonlinear features and reducing dimensionality. As a kernel method, kernel PCA … …Journal of Computer Science, Vol. 10, Issue 7 · 15 Feb 2014 · 8,721 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordImproving Term Extraction Using Particle Swarm Optimization TechniquesMohammad Syafrullah, Naomie SalimProblem statement: Term extraction is one of the layers in the ontology development process which has the task to extract all the terms contained in the input document automatically. The purpose of this process is to generate list of terms that are relevant to the domain of the input document. In the literature there are many approaches, techniques and algorithms … …Journal of Computer Science, Vol. 6, Issue 3 · 31 Mar 2010 · 7,138 accessesView PDFCite