{"id":68289,"date":"2015-11-26T15:36:20","date_gmt":"2015-11-26T06:36:20","guid":{"rendered":"https:\/\/www.waseda.jp\/inst\/research\/?p=68289"},"modified":"2019-01-22T15:38:29","modified_gmt":"2019-01-22T06:38:29","slug":"optimizing-marketing-communications-with-quantum-annealing-data-analysis","status":"publish","type":"post","link":"https:\/\/www.waseda.jp\/inst\/research\/news-en\/68289","title":{"rendered":"Optimizing marketing &#038; communications with quantum annealing data analysis"},"content":{"rendered":"<p>On November 20, Waseda University formed a research partnership with <a href=\"https:\/\/www.rco.recruit.co.jp\/\" target=\"_blank\">Recruit Communications<\/a> to develop a method for quantum annealing data analysis.<\/p>\n<h5>Goals of this research<\/h5>\n<p>Recruit Communications is a member of Recruit Group and specializes in web marketing, media production, advertising, and communications. In recent years, they have worked on marketing technology and research to find ways of maximizing marketing effectiveness.<\/p>\n<p>This research partnership hopes to maximize the effectiveness of marketing communications by developing a method for quantum annealing data analysis that takes into consideration program implementation and practical applicability.<\/p>\n<h5>Role of Waseda University<\/h5>\n<p>The <a href=\" http:\/\/www.waseda.jp\/wias\/\" target=\"_blank\">Waseda Institute for Advanced Study<\/a> will be in charge of developing logical constructions and Recruit Communications will work with Waseda to implement new methods of data analysis and evaluate performance.<\/p>\n<h5>What is quantum annealing?<\/h5>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-35113\" alt=\"ShuTanaka-eyecatchpic\" src=\"http:\/\/www.waseda.jp\/top\/assets\/uploads\/2015\/11\/ShuTanaka-eyecatchpic1.jpg\" width=\"1422\" height=\"1012\" \/><\/p>\n<p>Quantum annealing is a method for solving optimization problems through a process using quantum fluctuations. Quantum annealing is considered effective for solving non-linear optimization problems that have several localized solutions. It is also said to be useful for formulizing optimization problems in the field of machine learning.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>On November 20, Waseda University formed a research partnership with Recruit Communications to develop a metho [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":68290,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[95],"tags":[85,179,69],"class_list":["post-68289","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-en","tag-business-en","tag-research-en","tag-tech-en"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.waseda.jp\/inst\/research\/wp-json\/wp\/v2\/posts\/68289","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.waseda.jp\/inst\/research\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.waseda.jp\/inst\/research\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/inst\/research\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/inst\/research\/wp-json\/wp\/v2\/comments?post=68289"}],"version-history":[{"count":0,"href":"https:\/\/www.waseda.jp\/inst\/research\/wp-json\/wp\/v2\/posts\/68289\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.waseda.jp\/inst\/research\/wp-json\/wp\/v2\/media\/68290"}],"wp:attachment":[{"href":"https:\/\/www.waseda.jp\/inst\/research\/wp-json\/wp\/v2\/media?parent=68289"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.waseda.jp\/inst\/research\/wp-json\/wp\/v2\/categories?post=68289"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.waseda.jp\/inst\/research\/wp-json\/wp\/v2\/tags?post=68289"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}