{"id":636,"date":"2016-07-19T17:20:37","date_gmt":"2016-07-19T20:20:37","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=636"},"modified":"2016-07-19T17:20:37","modified_gmt":"2016-07-19T20:20:37","slug":"vol11-no1-art1","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/","title":{"rendered":"An Oscillatory Correlation Model for Semi-Supervised Classification"},"content":{"rendered":"<p><strong>T\u00edtulo:<\/strong> An Oscillatory Correlation Model for Semi-Supervised Classification<\/p>\n<p><strong>Autores:<\/strong> Quiles, Marcos G.; Basgalupp, M\u00e1rcio P.; Barros, Rodrigo C.<\/p>\n<p align=\"justify\"><strong>Resumo:<\/strong> This paper presents a new semi-supervised classification algorithm based on the oscillatory correlation theory. In this approach, the dataset is converted into a network whose nodes represent the samples and the edges represent the similarity among these samples. Each node in the network is modeled by an oscillator. The network clustering is given by the oscillators synchronization phenomenon, whereas the separation of oscillators that represent distinct clusters is induced by a global inhibitor. The previously labeled objects make use of the synchronization dynamics in order to propagate labels among their neighbors. Experiments performed with the proposed approach have shown promising results in a variety of datasets. It has shown to be capable of eventually outperforming traditional methods in the literature.<\/p>\n<p><strong>Palavras-chave:<\/strong> Oscillatory correlation; synchronization; semi-supervised learning<\/p>\n<p><strong>P\u00e1ginas:<\/strong> 8<\/p>\n<p><strong>C\u00f3digo DOI:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol11-no1-art1\">10.21528\/lmln-vol11-no1-art1<\/a><\/p>\n<p><strong>Artigo em PDF:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2016\/07\/vol11-no1-art1.pdf\" rel=\"\">vol11-no1-art1.pdf<\/a><\/p>\n<p><strong>Arquivo BibTex:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2016\/07\/vol11-no1-art1.bib\" rel=\"\">vol11-no1-art1.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>T\u00edtulo: An Oscillatory Correlation Model for Semi-Supervised Classification Autores: Quiles, Marcos G.; Basgalupp, M\u00e1rcio P.; Barros, Rodrigo C. Resumo: This paper presents a new semi-supervised classification algorithm based on the oscillatory correlation theory. In this approach, the dataset is converted <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":634,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-636","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>An Oscillatory Correlation Model for Semi-Supervised Classification - Learning and NonLinear Models<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"An Oscillatory Correlation Model for Semi-Supervised Classification - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"T\u00edtulo: An Oscillatory Correlation Model for Semi-Supervised Classification Autores: Quiles, Marcos G.; Basgalupp, M\u00e1rcio P.; Barros, Rodrigo C. Resumo: This paper presents a new semi-supervised classification algorithm based on the oscillatory correlation theory. In this approach, the dataset is converted Read More ...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/\" \/>\n<meta property=\"og:site_name\" content=\"Learning and NonLinear Models\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. tempo de leitura\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minuto\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/\",\"name\":\"An Oscillatory Correlation Model for Semi-Supervised Classification - Learning and NonLinear Models\",\"isPartOf\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#website\"},\"datePublished\":\"2016-07-19T20:20:37+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/#breadcrumb\"},\"inLanguage\":\"pt-BR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Browse issues\",\"item\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Learning &#038; Nonlinear Models &#8211; L&#038;NLM &#8211; Volume 11 &#8211; N\u00famero 1\",\"item\":\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"An Oscillatory Correlation Model for Semi-Supervised Classification\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#website\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/\",\"name\":\"Learning and NonLinear Models\",\"description\":\"\",\"publisher\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/sbia.org.br\/lnlm\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"pt-BR\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#organization\",\"name\":\"Learning and NonLinear Models\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"pt-BR\",\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/07\/logo-lnlm.png\",\"contentUrl\":\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/07\/logo-lnlm.png\",\"width\":398,\"height\":94,\"caption\":\"Learning and NonLinear Models\"},\"image\":{\"@id\":\"https:\/\/sbia.org.br\/lnlm\/#\/schema\/logo\/image\/\"}}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"An Oscillatory Correlation Model for Semi-Supervised Classification - Learning and NonLinear Models","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/","og_locale":"pt_BR","og_type":"article","og_title":"An Oscillatory Correlation Model for Semi-Supervised Classification - Learning and NonLinear Models","og_description":"T\u00edtulo: An Oscillatory Correlation Model for Semi-Supervised Classification Autores: Quiles, Marcos G.; Basgalupp, M\u00e1rcio P.; Barros, Rodrigo C. Resumo: This paper presents a new semi-supervised classification algorithm based on the oscillatory correlation theory. In this approach, the dataset is converted Read More ...","og_url":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/","og_site_name":"Learning and NonLinear Models","twitter_card":"summary_large_image","twitter_misc":{"Est. tempo de leitura":"1 minuto"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/","url":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/","name":"An Oscillatory Correlation Model for Semi-Supervised Classification - Learning and NonLinear Models","isPartOf":{"@id":"https:\/\/sbia.org.br\/lnlm\/#website"},"datePublished":"2016-07-19T20:20:37+00:00","breadcrumb":{"@id":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/#breadcrumb"},"inLanguage":"pt-BR","potentialAction":[{"@type":"ReadAction","target":["https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/vol11-no1-art1\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Browse issues","item":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/"},{"@type":"ListItem","position":2,"name":"Learning &#038; Nonlinear Models &#8211; L&#038;NLM &#8211; Volume 11 &#8211; N\u00famero 1","item":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol11-no1\/"},{"@type":"ListItem","position":3,"name":"An Oscillatory Correlation Model for Semi-Supervised Classification"}]},{"@type":"WebSite","@id":"https:\/\/sbia.org.br\/lnlm\/#website","url":"https:\/\/sbia.org.br\/lnlm\/","name":"Learning and NonLinear Models","description":"","publisher":{"@id":"https:\/\/sbia.org.br\/lnlm\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/sbia.org.br\/lnlm\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"pt-BR"},{"@type":"Organization","@id":"https:\/\/sbia.org.br\/lnlm\/#organization","name":"Learning and NonLinear Models","url":"https:\/\/sbia.org.br\/lnlm\/","logo":{"@type":"ImageObject","inLanguage":"pt-BR","@id":"https:\/\/sbia.org.br\/lnlm\/#\/schema\/logo\/image\/","url":"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/07\/logo-lnlm.png","contentUrl":"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2021\/07\/logo-lnlm.png","width":398,"height":94,"caption":"Learning and NonLinear Models"},"image":{"@id":"https:\/\/sbia.org.br\/lnlm\/#\/schema\/logo\/image\/"}}]}},"_links":{"self":[{"href":"https:\/\/sbia.org.br\/lnlm\/wp-json\/wp\/v2\/pages\/636","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sbia.org.br\/lnlm\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sbia.org.br\/lnlm\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sbia.org.br\/lnlm\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sbia.org.br\/lnlm\/wp-json\/wp\/v2\/comments?post=636"}],"version-history":[{"count":0,"href":"https:\/\/sbia.org.br\/lnlm\/wp-json\/wp\/v2\/pages\/636\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/sbia.org.br\/lnlm\/wp-json\/wp\/v2\/pages\/634"}],"wp:attachment":[{"href":"https:\/\/sbia.org.br\/lnlm\/wp-json\/wp\/v2\/media?parent=636"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}