{"id":13638,"date":"2022-01-27T15:00:09","date_gmt":"2022-01-27T14:00:09","guid":{"rendered":"https:\/\/kinit.sk\/?post_type=publication&#038;p=13638"},"modified":"2026-04-23T15:03:48","modified_gmt":"2026-04-23T13:03:48","slug":"towards-symbolic-time-series-representation-improved-by-kernel-density-estimators","status":"publish","type":"publication","link":"https:\/\/kinit.sk\/sk\/publikacia\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\/","title":{"rendered":"Towards Symbolic Time Series Representation Improved by Kernel Density Estimators"},"content":{"rendered":"<div id=\"\" class=\"element core-paragraph\">\n<p><strong>Kloska, M., Rozinajova, V.<\/strong><\/p>\n<\/div>\n\n<div id=\"\" class=\"element core-paragraph\">\n<p>This paper deals with symbolic time series representation. It builds up on the popular mapping technique Symbolic Aggregate approXimation algorithm (SAX), which is extensively utilized in sequence classification, pattern mining, anomaly detection, time series indexing and other data mining tasks. However, the disadvantage of this method is, that it works reliably only for time series with Gaussian-like distribution. In our previous work (Kloska and Rozinajova, dwSAX, 2020) we have proposed an improvement of SAX, called dwSAX, which can deal with Gaussian as well as non-Gaussian data distribution. Recently we have made further progress in our solution &#8211; edwSAX. Our goal was to optimally cover the information space by means of sufficient alphabet utilization; and to satisfy lower bounding criterion as tight as possible. We describe here our approach, including evaluation on commonly employed tasks such as time series reconstruction error and Euclidean distance lower bounding with promising improvements over SAX.<\/p>\n<\/div>\n\n<div id=\"\" class=\"element core-paragraph  margin-bottom-0\">\n<p class=\"margin-bottom-0\">Cite: Kloska, M., Rozinajova, V. Towards Symbolic Time Series Representation Improved by Kernel Density Estimators. Transactions on Large-Scale Data- and Knowledge-Centered Systems (2022). DOI: <a href=\"https:\/\/doi.org\/10.1007\/978-3-662-64553-6_2\" target=\"_blank\" rel=\"noreferrer noopener\">10.1007\/978-3-662-64553-6_2<\/a><\/p>\n<\/div>\n\n<div id=\"\" class=\"element acf-columns margin-top-0 margin-bottom-0 less-space\">\n<section class=\"columns  margin-top-0 margin-bottom-0 less-space\"  >\n\t<div class=\"wrapper-out\">\n\t\t<div class=\"wrapper-in\">\n\t\t\t<div class=\"in cf\">\n\t\t\t\t<div class=\"element-inner\">\n\t\t\t\t\t\t\t\t\t\t<div class=\"columns columns2\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"column\">\n\t\t\t\t\t\t\t\t\t<div class=\"inner\">\n\t\t\t\t\t\t\t\t\t\t<p><i>KIniT basic research in 2021 and 2022 has also been supported by\u00a0<\/i><\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"column\">\n\t\t\t\t\t\t\t\t\t<div class=\"inner\">\n\t\t\t\t\t\t\t\t\t\t<p><img decoding=\"async\" class=\"alignnone wp-image-14975 lazyload\" role=\"img\" data-src=\"https:\/\/kinit.sk\/wp-content\/uploads\/2022\/03\/logo-minedu-en.svg\" alt=\"\" width=\"193\" height=\"61\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 193px; --smush-placeholder-aspect-ratio: 193\/61;\" \/><\/p>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section> \n<\/div>","protected":false},"featured_media":0,"template":"","meta":{"_acf_changed":false,"footnotes":""},"categories":[81,349],"class_list":["post-13638","publication","type-publication","status-publish","hentry","category-data-analytics-for-green-energy-sk","category-2022-sk"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Towards Symbolic Time Series Representation Improved by Kernel Density Estimators - KInIT<\/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:\/\/kinit.sk\/sk\/publikacia\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\/\" \/>\n<meta property=\"og:locale\" content=\"sk_SK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Towards Symbolic Time Series Representation Improved by Kernel Density Estimators - KInIT\" \/>\n<meta property=\"og:description\" content=\"Kloska, M., Rozinajova, V. This paper deals with symbolic time series representation. It builds up on the popular mapping technique Symbolic Aggregate approXimation algorithm (SAX), which is extensively utilized in...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/kinit.sk\/sk\/publikacia\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\/\" \/>\n<meta property=\"og:site_name\" content=\"KInIT\" \/>\n<meta property=\"article:modified_time\" content=\"2026-04-23T13:03:48+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/kinit.sk\/wp-content\/uploads\/2021\/03\/KINIT_Sharepic.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"628\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@kinit\" \/>\n<meta name=\"twitter:label1\" content=\"Predpokladan\u00fd \u010das \u010d\u00edtania\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 min\u00fata\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/kinit.sk\\\/sk\\\/publikacia\\\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\\\/\",\"url\":\"https:\\\/\\\/kinit.sk\\\/sk\\\/publikacia\\\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\\\/\",\"name\":\"Towards Symbolic Time Series Representation Improved by Kernel Density Estimators - KInIT\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/kinit.sk\\\/#website\"},\"datePublished\":\"2022-01-27T14:00:09+00:00\",\"dateModified\":\"2026-04-23T13:03:48+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/kinit.sk\\\/sk\\\/publikacia\\\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\\\/#breadcrumb\"},\"inLanguage\":\"sk-SK\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/kinit.sk\\\/sk\\\/publikacia\\\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\\\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/kinit.sk\\\/sk\\\/publikacia\\\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/kinit.sk\\\/sk\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Data Analytics for Green Energy\",\"item\":\"https:\\\/\\\/kinit.sk\\\/category\\\/data-analytics-for-green-energy\\\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Towards Symbolic Time Series Representation Improved by Kernel Density Estimators\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/kinit.sk\\\/#website\",\"url\":\"https:\\\/\\\/kinit.sk\\\/\",\"name\":\"KInIT\",\"description\":\"Vyu\u017e\u00edvame v\u00fdskum pre \u013eud\u00ed a priemysel\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/kinit.sk\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"sk-SK\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Towards Symbolic Time Series Representation Improved by Kernel Density Estimators - KInIT","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:\/\/kinit.sk\/sk\/publikacia\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\/","og_locale":"sk_SK","og_type":"article","og_title":"Towards Symbolic Time Series Representation Improved by Kernel Density Estimators - KInIT","og_description":"Kloska, M., Rozinajova, V. This paper deals with symbolic time series representation. It builds up on the popular mapping technique Symbolic Aggregate approXimation algorithm (SAX), which is extensively utilized in...","og_url":"https:\/\/kinit.sk\/sk\/publikacia\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\/","og_site_name":"KInIT","article_modified_time":"2026-04-23T13:03:48+00:00","og_image":[{"width":1200,"height":628,"url":"https:\/\/kinit.sk\/wp-content\/uploads\/2021\/03\/KINIT_Sharepic.png","type":"image\/png"}],"twitter_card":"summary_large_image","twitter_site":"@kinit","twitter_misc":{"Predpokladan\u00fd \u010das \u010d\u00edtania":"1 min\u00fata"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/kinit.sk\/sk\/publikacia\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\/","url":"https:\/\/kinit.sk\/sk\/publikacia\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\/","name":"Towards Symbolic Time Series Representation Improved by Kernel Density Estimators - KInIT","isPartOf":{"@id":"https:\/\/kinit.sk\/#website"},"datePublished":"2022-01-27T14:00:09+00:00","dateModified":"2026-04-23T13:03:48+00:00","breadcrumb":{"@id":"https:\/\/kinit.sk\/sk\/publikacia\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\/#breadcrumb"},"inLanguage":"sk-SK","potentialAction":[{"@type":"ReadAction","target":["https:\/\/kinit.sk\/sk\/publikacia\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/kinit.sk\/sk\/publikacia\/towards-symbolic-time-series-representation-improved-by-kernel-density-estimators\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/kinit.sk\/sk\/"},{"@type":"ListItem","position":2,"name":"Data Analytics for Green Energy","item":"https:\/\/kinit.sk\/category\/data-analytics-for-green-energy\/"},{"@type":"ListItem","position":3,"name":"Towards Symbolic Time Series Representation Improved by Kernel Density Estimators"}]},{"@type":"WebSite","@id":"https:\/\/kinit.sk\/#website","url":"https:\/\/kinit.sk\/","name":"KInIT","description":"Vyu\u017e\u00edvame v\u00fdskum pre \u013eud\u00ed a priemysel","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/kinit.sk\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"sk-SK"}]}},"_links":{"self":[{"href":"https:\/\/kinit.sk\/sk\/wp-json\/wp\/v2\/publication\/13638","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/kinit.sk\/sk\/wp-json\/wp\/v2\/publication"}],"about":[{"href":"https:\/\/kinit.sk\/sk\/wp-json\/wp\/v2\/types\/publication"}],"version-history":[{"count":5,"href":"https:\/\/kinit.sk\/sk\/wp-json\/wp\/v2\/publication\/13638\/revisions"}],"predecessor-version":[{"id":41989,"href":"https:\/\/kinit.sk\/sk\/wp-json\/wp\/v2\/publication\/13638\/revisions\/41989"}],"wp:attachment":[{"href":"https:\/\/kinit.sk\/sk\/wp-json\/wp\/v2\/media?parent=13638"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/kinit.sk\/sk\/wp-json\/wp\/v2\/categories?post=13638"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}