{"id":1434,"date":"2021-12-20T16:16:26","date_gmt":"2021-12-20T16:16:26","guid":{"rendered":"https:\/\/ifipaiai.org\/2022\/?page_id=1434"},"modified":"2022-01-12T16:02:57","modified_gmt":"2022-01-12T16:02:57","slug":"mhdw","status":"publish","type":"page","link":"https:\/\/ifipaiai.org\/2022\/workshops\/mhdw\/","title":{"rendered":"MHDW Workshop"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"1434\" class=\"elementor elementor-1434\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1130a45 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1130a45\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1815ea3\" data-id=\"1815ea3\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-4901938 elementor-widget elementor-widget-heading\" data-id=\"4901938\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.20.0 - 13-03-2024 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h4 class=\"elementor-heading-title elementor-size-default\">The 11th Workshop on<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4197059 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4197059\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-49cd4d0e\" data-id=\"49cd4d0e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-592eb658 elementor-widget elementor-widget-heading\" data-id=\"592eb658\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Mining Humanistic Data (MHDW)<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-78f3a71 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"78f3a71\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-a55cd12\" data-id=\"a55cd12\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5b96ce4 elementor-button-info elementor-align-center elementor-widget elementor-widget-button\" data-id=\"5b96ce4\" data-element_type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;none&quot;}\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/conferences.cwa.gr\/mhdw2022\/\" target=\"_blank\" rel=\"nofollow\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-icon elementor-align-icon-left\">\n\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-globe\"><\/i>\t\t\t<\/span>\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Website<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-6fed02ba elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6fed02ba\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-705817b6\" data-id=\"705817b6\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-62f8c785 elementor-widget elementor-widget-text-editor\" data-id=\"62f8c785\" data-element_type=\"widget\" data-settings=\"{&quot;_animation&quot;:&quot;none&quot;}\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.20.0 - 13-03-2024 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<div class=\"et_pb_column et_pb_column_4_4 et_pb_column_2 et_pb_css_mix_blend_mode_passthrough et-last-child\"><div class=\"et_pb_module et_pb_text et_pb_text_1 et_pb_text_align_left et_pb_bg_layout_light\"><div class=\"et_pb_text_inner\"><p><\/p><p>The Mining Humanistic Data Workshop (MHDW) aims to bring together interdisciplinary approaches that focus on the application of innovative as well as existing artificial intelligence, data matching, fusion and mining and knowledge discovery and management techniques to data derived from all areas of Humanistic Sciences.<\/p><p>MHDW 2022 will be supported by experts in numerous fields of the theme of the workshop:<\/p><p><strong><span>Program chairs<\/span><\/strong><\/p><ul><li>Andreas Kanavos, Ionian University, Greece<\/li><li>Christos Makris, University of Patras, Greece<\/li><li>Phivos Mylonas, Ionian University, Greece<\/li><\/ul><p><strong>Steering Committe<\/strong><\/p><ul><li>Ioannis Karydis, Ionian University, Greece<\/li><li>Katia Lida Kermanidis, Ionian University, Greece<\/li><li>Spyros Sioutas, University of Patras, Greece<\/li><\/ul><p><strong>Steering Committe<\/strong><\/p><ul><li>Ioannis Anagnostopoulos, University of Thessaly, Greece<\/li><li>Ioannis Hatzilygeroudis, University of Patras, Greece<\/li><li>Andreas Kanavos, Ionian University, Greece<\/li><li>Ioannis Karydis, Ionian University, Greece<\/li><li>Katia Lida Kermanidis, Ionian University, Greece<\/li><li>Andreas Komninos, University of Thessaly, Greece<\/li><li>Sotiris Kotsiantis, University of Patras, Greece<\/li><li>Christos Makris, University of Patras, Greece<\/li><li>Seferina Mavroudi, University of Patras, Greece<\/li><li>Phivos Mylonas, Ionian University, Greece<\/li><li>Spyros Sioutas, University of Patras, Greece<\/li><li>Eleanna Kafeza, College of Technological Innovation, Zayed University, <br \/>Abu Dhabi<\/li><\/ul><p><strong><\/strong><\/p><p><strong>Aim of MHDW <\/strong><\/p><p>The abundance of available data that is retrieved from or is related to the areas of Humanities and the human condition challenges the research community in processing and analyzing it. The aim is two-fold: on the one hand, to extract knowledge that will help understand human behavior, creativity, way of thinking, reasoning, learning, decision making, socializing and even biological processes; on the other hand, to exploit the extracted knowledge by incorporating it into intelligent systems that will support humans in their everyday activities.<\/p><p>The nature of humanistic data can be multimodal, semantically heterogeneous, dynamic, time and space-dependent, and highly complicated. Translating humanistic information, e.g. behavior, state of mind, artistic creation, linguistic utterance, learning and genomic information into numerical or categorical low-level data is a significant challenge on its own. New techniques, appropriate to deal with this type of data, need to be proposed and existing ones adapted to its special characteristics.<\/p><p>The workshop aims to bring together interdisciplinary approaches that focus on the application of innovative as well as existing data matching, fusion and mining and knowledge discovery and management techniques (like decision rules, decision trees, association rules, ontologies and alignments, clustering, filtering, learning, classifier systems, neural networks, support vector machines, preprocessing, post processing, feature selection, visualization techniques) to data derived from all areas of Humanistic Sciences, e.g. linguistic, historical, behavioral, psychological, artistic, musical, educational, social etc., Ubiquitous Computing and Bioinformatics. In that sense, MHDW is an astute match for AIAI\u2019s theme since it covers domains such as artificial intelligence\u2019s theoretical advances, artificial intelligence applications, knowledge engineering, signal processing techniques &amp; knowledge extraction, multimedia, and graphics &amp; Artificial Intelligence that are of related to the topics of AIAI, with a focus on the humanities.<\/p><\/div><\/div><\/div>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8816594 elementor-widget elementor-widget-text-editor\" data-id=\"8816594\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Topics of interest<\/strong> of MHDW include (but are not limited to):<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3283797 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3283797\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-89c3939\" data-id=\"89c3939\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-329230a elementor-widget elementor-widget-text-editor\" data-id=\"329230a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"et_pb_module et_pb_text et_pb_text_3  et_pb_text_align_left et_pb_bg_layout_light\"><div class=\"et_pb_text_inner\"><ul><li>Humanistic data collection and interpretation<\/li><li><span>Data pre-processing<\/span><\/li><li><span>Feature selection methodologies<\/span><\/li><li>Supervised or unsupervised learning of humanistic knowledge<\/li><li><span>Clustering\/Classification techniques<\/span><\/li><li><span>Fuzzy modeling<\/span><\/li><li><span>Heterogeneous data fusion<\/span><\/li><li><span>Knowledge representation and reasoning<\/span><\/li><li><span>Linguistic data mining<\/span><\/li><li><span>Educational data mining<\/span><\/li><li><span>Music information retrieval<\/span><\/li><li><span>Data-driven profiling\/ personalization<\/span><\/li><li><span>User modeling<\/span><\/li><li><span>Behavior prediction<\/span><\/li><li><span>Recommender systems<\/span><\/li><li><span>Web sentiment analysis<\/span><\/li><li><span>Social data mining<\/span><\/li><li><span>Data visualization techniques<\/span><\/li><li>Integration of data mining results into real-world applications with humanistic context<\/li><li><span>Ontologies, ontology matching and alignment<\/span><\/li><\/ul><\/div><\/div>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-5bf3758\" data-id=\"5bf3758\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-57b9af3 elementor-widget elementor-widget-text-editor\" data-id=\"57b9af3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"et_pb_module et_pb_text et_pb_text_4  et_pb_text_align_left et_pb_bg_layout_light\"><div class=\"et_pb_text_inner\"><ul><li>Mining humanistic data in the cloud<\/li><li><span>Game data mining<\/span><\/li><li><span>Virtual-world data mining<\/span><\/li><li><span>Speech and audio data processing<\/span><\/li><li>Data mining techniques for knowledge discovery<\/li><li><span>Biomedical data mining<\/span><\/li><li><span>Bioinformatics<\/span><\/li><li>Content creation, annotation and modeling for semantic and social web<\/li><li>Computational intelligence for media adaptation and personalization<\/li><li>Semantics-driven indexing and retrieval of multimedia contents<\/li><li><span>Semantic context modeling and extraction<\/span><\/li><li><span>Context-aware applications<\/span><\/li><li><span>Social web economics and business<\/span><\/li><li>Privacy\/security issues in social and personalized applications<\/li><li>Privacy preserving data mining and social networks<\/li><li><span>Social data analytic<\/span>s<\/li><\/ul><\/div><\/div>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4f1438f6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4f1438f6\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-7c1189b8\" data-id=\"7c1189b8\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-62b201ba elementor-widget elementor-widget-text-editor\" data-id=\"62b201ba\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Reviewing process<\/strong><\/p><p>MHDW has long utilized a dingle-blind review process with approx. 3 reviews per submission using the widely accepted EasyChair software. Each review is finally to be checked by a member of the PC, prior to dispatching to authors, in order to verify the high level of comments made to authors.<\/p><p><strong>Participation<\/strong><\/p><p>MHDW\u2019s 2022 edition will be the 10th in a series of high quality participations. The evolution of the submissions made in MHDW makes us confident that about 15-20 submissions will be made of which only the highest quality top 50% will be selected for publication.<\/p><p><strong>MHDW\u2019s continuation<\/strong><\/p><p>MHDW aims to bridge the domains of data mining and artificial intelligence with the Humanistic studies, a domain that despite receiving less of a spot-light is as crucial in our lives as ever. Current developments in ICT have, similarly to Medicine and Science &amp; Technology, lead to increased data creation rates in the Humanities as well and MHDW provides a theoretical and applied platform for researches to identify issues with these data and develop methodologies to address them. If is for these reasons that we believe that\u00a0 MHDW is as timely as ever, and thus request AIAI to support its 2022 edition.<\/p><p><b>Important dates<\/b><\/p><p>Please visit <a href=\"https:\/\/ifipaiai.org\/2022\/important-dates\/\">AIAI 2022 important dates<\/a> to be informed about the submission deadlines.<\/p><p><b>Submission instructions<\/b><span><\/span><\/p><p>Submission details can be found at AIAI conference<span>\u00a0<\/span><a href=\"https:\/\/ifipaiai.org\/2022\/paper-submission\/\">submission page<\/a>.<\/p><p>All papers should be submitted either in a doc\/docx or in a pdf form and will be peer reviewed by at least 2 academic referees. Contributing authors must follow the<span>\u00a0<\/span><a href=\"https:\/\/ifipaiai.org\/2022\/calls-for-papers\/\">AIAI2022\u2019s paper format guidelines<\/a><span>\u00a0<\/span>as far as the IFIP AICT file format.<\/p><p><span>Papers will be peer reviewed by at least two (-2-) members of the workshop\u2019s program committee.<\/span><\/p><p><span>Accepted papers will be published in the Proceedings of AIAI VOLUME 2, under the Springer IFIP AICT Series.<\/span><\/p><p><span lang=\"EN-US\">You can submit you MHDW paper here<span>\u00a0<\/span><a href=\"http:\/\/www.easyacademia.org\/aiai2022\" target=\"_blank\" data-saferedirecturl=\"https:\/\/www.google.com\/url?q=http:\/\/www.easyacademia.org\/aiai2022&amp;source=gmail&amp;ust=1640959020019000&amp;usg=AOvVaw0xTTG6k6DEqtrHqlo61bP0\" rel=\"noopener\">http:\/\/www.easyacademia.org\/<wbr \/>aiai2022<\/a>.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>The 11th Workshop on Mining Humanistic Data (MHDW) Website The Mining Humanistic Data Workshop (MHDW) aims to bring together interdisciplinary approaches that focus on the application of innovative as well as existing artificial intelligence, data matching, fusion and mining and knowledge discovery and management techniques to data derived from all [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":268,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/ifipaiai.org\/2022\/wp-json\/wp\/v2\/pages\/1434"}],"collection":[{"href":"https:\/\/ifipaiai.org\/2022\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ifipaiai.org\/2022\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ifipaiai.org\/2022\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ifipaiai.org\/2022\/wp-json\/wp\/v2\/comments?post=1434"}],"version-history":[{"count":38,"href":"https:\/\/ifipaiai.org\/2022\/wp-json\/wp\/v2\/pages\/1434\/revisions"}],"predecessor-version":[{"id":1749,"href":"https:\/\/ifipaiai.org\/2022\/wp-json\/wp\/v2\/pages\/1434\/revisions\/1749"}],"up":[{"embeddable":true,"href":"https:\/\/ifipaiai.org\/2022\/wp-json\/wp\/v2\/pages\/268"}],"wp:attachment":[{"href":"https:\/\/ifipaiai.org\/2022\/wp-json\/wp\/v2\/media?parent=1434"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}