{"id":4802,"date":"2018-01-02T08:00:25","date_gmt":"2018-01-02T07:00:25","guid":{"rendered":"http:\/\/www.obsidiansoft.com\/?p=4802"},"modified":"2023-09-27T11:18:16","modified_gmt":"2023-09-27T09:18:16","slug":"interpretacion-automatica-de-indicadores-de-gestion-de-servicios","status":"publish","type":"post","link":"https:\/\/www.obsidiansoft.com\/en\/blog-en-2\/interpretacion-automatica-de-indicadores-de-gestion-de-servicios\/","title":{"rendered":"Automatic interpretation of service management indicators"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>[vc_row css_animation=&#8221;&#8221; row_type=&#8221;row&#8221; use_row_as_full_screen_section=&#8221;no&#8221; type=&#8221;full_width&#8221; angled_section=&#8221;no&#8221; text_align=&#8221;left&#8221; background_image_as_pattern=&#8221;without_pattern&#8221;][vc_column][vc_column_text]<\/p>\n<h2>Presentation at GigaTIC2017 on artificial intelligence techniques for the automatic interpretation of service management indicators<\/h2>\n<p><!-- paragraph -->Alberto Bugar\u00edn, professor of artificial intelligence, and Diego Berea, Director of Obsidian, gave a presentation about the use of data2text NGL for the automatic interpretation of service management indicators implemented in Obsidian. This session was part of GigaTIC2017, an event organized by iTSMF and ISACA.<\/p>\n<p>Below is the video of the presentation, which currently has 37319 visits on YouTube and 354 likes.<\/p>\n<p>If you wish to be updated about new videos posted by Obsidian, <a href=\"https:\/\/www.youtube.com\/channel\/UCCbaQSQvLT9et2a1eGvohfg?sub_confirmation=1\" target=\"_blank\">subscribe to our channel<\/a> and YouTube will notify you whenever new content is available.<\/p>\n<div class=\"epyt-video-wrapper\"><iframe loading=\"lazy\"  id=\"_ytid_43472\"  width=\"1060\" height=\"795\"  data-origwidth=\"1060\" data-origheight=\"795\" src=\"https:\/\/www.youtube.com\/embed\/Ri1reIYNVUU?enablejsapi=1&autoplay=0&cc_load_policy=1&cc_lang_pref=&iv_load_policy=1&loop=0&rel=1&fs=1&playsinline=1&autohide=2&hl=en_US&theme=dark&color=red&controls=1&disablekb=0&\" class=\"__youtube_prefs__  no-lazyload\" data-vol=\"50\"  title=\"YouTube player\"  allow=\"fullscreen; accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen data-no-lazy=\"1\" data-skipgform_ajax_framebjll=\"\"><\/iframe><\/div>\n<h2>Artificial intelligence techniques for the automatic interpretation of service management indicators<\/h2>\n<p><!-- paragraph -->First, this presentation sets out the most common methodologies to implement a data2text NLG system. Then, it shows multiple examples of its practical application for the automatic interpretation of service management indicators. These examples are based on data2text implementation in Obsidian, which includes service desk metrics as well as availability, capacity, or service level indicators. Now it is possible to obtain explanatory reports in real time based on data from tools. This is one of the main advantages of this type of system: Less analytical effort is required of the user.<\/p>\n<h2>Automatic data2text natural language generation systems in Obsidian<\/h2>\n<p><!-- paragraph -->There are several disciplines of artificial intelligence that relate to natural language processing (NLP). Out of these, one particular subset concerns techniques of automatic generation of natural language (NLG).<\/p>\n<p>In recent years, intensive research has been carried out in these areas. As a result, researchers have developed and deployed different software programs, which have even been tested in real environments with satisfactory results.<\/p>\n<p>Gartner predicts that, by 2018, NLG will be present in about 90% of BI market tools.<\/p>\n<p>In this sense, the management of ITSM services offers an extremely rich context for the application of NLG techniques. There are multiple actors (technicians, managers or directors), each with different information needs. These may be technical specifications, service performance values or simply information about whether the service level agreed with the customer has been accomplished. But all this information can be extracted from corporate service desk and monitoring tools. So, NLG techniques attempt to help the user by processing these data and displaying a written interpretation according to each user&#8217;s role.<\/p>\n<p>More information on the <a href=\"https:\/\/www.obsidiansoft.com\/en\/data2text\/\">data2text functionalities of Obsidian<\/a>.<\/p>\n<h2>Further information<\/h2>\n<p><!-- paragraph -->[\/vc_column_text][\/vc_column][\/vc_row][vc_row css_animation=&#8221;&#8221; row_type=&#8221;row&#8221; use_row_as_full_screen_section=&#8221;no&#8221; type=&#8221;full_width&#8221; angled_section=&#8221;no&#8221; text_align=&#8221;left&#8221; background_image_as_pattern=&#8221;without_pattern&#8221;][vc_column width=&#8221;1\/2&#8243;][vc_column_text]If you want more information about the automatic interpretation of service management indicators with Obsidian, or other features of our platform, please contact us via the attached form.<\/p>\n<p><strong>NOTE<\/strong> Only professional e-mail addresses are accepted. Requests from gmail, yahoo, hotmail, etc. accounts will not be processed.<\/p>\n<p>The personal data collected via the form will be used to process your request. You may exercise your rights of access, rectification and cancellation by writing to Obsidian Soft, calle M\u00e9ndez \u00c1lvaro, 20 \u00b7 18045 \u00b7 Madrid.<\/p>\n<p>You can also subscribe to our <a class=\"inbound-track-link\" href=\"https:\/\/www.obsidiansoft.com\/en\/newsletter\/\" target=\"_blank\" rel=\"noopener noreferrer\">newsletter<\/a> or to our <a href=\"https:\/\/www.youtube.com\/channel\/UCCbaQSQvLT9et2a1eGvohfg?sub_confirmation=1\" target=\"_blank\">YouTube channel<\/a>, which currently has 1570 subscribers. 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Obsidian<\/p>\n","protected":false},"author":12,"featured_media":7168,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","om_disable_all_campaigns":false,"inline_featured_image":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[102],"tags":[],"class_list":["post-4802","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog-en-2"],"_links":{"self":[{"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/posts\/4802","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/users\/12"}],"replies":[{"embeddable":true,"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/comments?post=4802"}],"version-history":[{"count":2,"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/posts\/4802\/revisions"}],"predecessor-version":[{"id":7728,"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/posts\/4802\/revisions\/7728"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/media\/7168"}],"wp:attachment":[{"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/media?parent=4802"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/categories?post=4802"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.obsidiansoft.com\/en\/wp-json\/wp\/v2\/tags?post=4802"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}