{"id":714577,"date":"2020-12-30T03:20:40","date_gmt":"2020-12-30T11:20:40","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-group&#038;p=714577"},"modified":"2024-04-08T02:23:37","modified_gmt":"2024-04-08T09:23:37","slug":"data-knowledge-intelligence","status":"publish","type":"msr-group","link":"https:\/\/www.microsoft.com\/en-us\/research\/group\/data-knowledge-intelligence\/","title":{"rendered":"Data, Knowledge, and Intelligence"},"content":{"rendered":"<section class=\"mb-3 moray-highlight\">\n\t<div class=\"card-img-overlay mx-lg-0\">\n\t\t<div class=\"card-background  has-background-grey card-background--full-bleed\">\n\t\t\t\t\t<\/div>\n\t\t<!-- Foreground -->\n\t\t<div class=\"card-foreground d-flex mt-md-n5 my-lg-5 px-g px-lg-0\">\n\t\t\t<!-- Container -->\n\t\t\t<div class=\"container d-flex mt-md-n5 my-lg-5 \">\n\t\t\t\t<!-- Card wrapper -->\n\t\t\t\t<div class=\"w-100 w-lg-col-5\">\n\t\t\t\t\t<!-- Card -->\n\t\t\t\t\t<div class=\"card material-md-card py-5 px-md-5\">\n\t\t\t\t\t\t<div class=\"card-body \">\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n<h1 class=\"wp-block-heading h2\" id=\"data-knowledge-and-intelligence\">Data, Knowledge, and Intelligence<\/h1>\n\n\t\t\t\t\t\t<\/div>\n\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\n\n\n\n\n<p>The goal of our research on data and knowledge is to democratize data intelligence to empower people and organizations to derive insights, learn and share knowledge, and build intelligence to turn data into action. Regardless of the various forms of data, understanding, generation, and interaction are the three common themes threading through the research topics on data and knowledge in different domains. Data understanding aims to achieve semantic understanding of various types of data. Data generation is targeted at automatic content generation based on users\u2019 needs. Interaction with data aims to create unparalleled user experiences working with data.<\/p>\n<p>Data, Knowledge, and Intelligence (DKI)\u00a0is an interdisciplinary research area with active research in Artificial Intelligence (AI) and Machine Learning, Data Mining and Data Analytics,\u00a0<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/group\/knowledge-computing\/\">Knowledge Computing<\/a>,\u00a0NLP,\u00a0information visualization,\u00a0and\u00a0<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/group\/software-analytics\/\">Software Analytics<\/a>.\u00a0The research in DKI is also grounded as we get data and inspiration from real problems in different domains as well as apply our research results to make real-world impact.<\/p>\n\t<div data-wp-context='{\"items\":[]}' data-wp-interactive=\"msr\/accordion\">\n\t\t\t\t\t<div class=\"clearfix\">\n\t\t\t\t<div\n\t\t\t\t\tclass=\"btn-group align-items-center mb-g float-sm-right\"\n\t\t\t\t\tdata-bi-aN=\"accordion-collapse-controls\"\n\t\t\t\t>\n\t\t\t\t\t<button\n\t\t\t\t\t\tclass=\"btn btn-link m-0\"\n\t\t\t\t\t\tdata-bi-cN=\"Expand all\"\n\t\t\t\t\t\tdata-wp-bind--aria-controls=\"state.ariaControls\"\n\t\t\t\t\t\tdata-wp-bind--aria-expanded=\"state.ariaExpanded\"\n\t\t\t\t\t\tdata-wp-bind--disabled=\"state.isAllExpanded\"\n\t\t\t\t\t\tdata-wp-class--inactive=\"state.isAllExpanded\"\n\t\t\t\t\t\tdata-wp-on--click=\"actions.onExpandAll\"\n\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t>\n\t\t\t\t\t\tExpand all\t\t\t\t\t<\/button>\n\t\t\t\t\t<span aria-hidden=\"true\"> | <\/span>\n\t\t\t\t\t<button\n\t\t\t\t\t\tclass=\"btn btn-link m-0\"\n\t\t\t\t\t\tdata-bi-cN=\"Collapse all\"\n\t\t\t\t\t\tdata-wp-bind--aria-controls=\"state.ariaControls\"\n\t\t\t\t\t\tdata-wp-bind--aria-expanded=\"state.ariaExpanded\"\n\t\t\t\t\t\tdata-wp-bind--disabled=\"state.isAllCollapsed\"\n\t\t\t\t\t\tdata-wp-class--inactive=\"state.isAllCollapsed\"\n\t\t\t\t\t\tdata-wp-on--click=\"actions.onCollapseAll\"\n\t\t\t\t\t\ttype=\"button\"\n\t\t\t\t\t>\n\t\t\t\t\t\tCollapse all\t\t\t\t\t<\/button>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t<ul class=\"msr-accordion\">\n\t\t\t\t\t\t\t\t<li class=\"m-0\" data-wp-context='{\"id\":\"accordion-content-2\"}' data-wp-init=\"callbacks.init\">\n\t\t<div class=\"accordion-header\">\n\t\t\t<button\n\t\t\t\taria-controls=\"accordion-content-2\"\n\t\t\t\tclass=\"btn btn-collapse\"\n\t\t\t\tdata-wp-bind--aria-expanded=\"state.isExpanded\"\n\t\t\t\tdata-wp-on--click=\"actions.onClick\"\n\t\t\t\tid=\"accordion-button-1\"\n\t\t\t\ttype=\"button\"\n\t\t\t>\n\t\t\t\tResearch Topics\t\t\t<\/button>\n\t\t<\/div>\n\t\t<div\n\t\t\taria-labelledby=\"accordion-button-1\"\n\t\t\tclass=\"msr-accordion__content\"\n\t\t\tdata-wp-bind--inert=\"!state.isExpanded\"\n\t\t\tdata-wp-run=\"callbacks.run\"\n\t\t\tid=\"accordion-content-2\"\n\t\t>\n\t\t\t<div class=\"msr-accordion__body\">\n\t\t\t\t<p><b>Data Analytics Research<\/b><\/p><p>We focus on research about understanding data, modeling analysis process, and their combined techniques for automatically generating analytical artifacts such as insights and analysis reports out of data. Specifically, for data we currently focus on representation learning and schematization of human-crafted data artifacts, especially for (semi-)structured data such as table, questionnaire, etc.; for analytics we currently focus on insights mining, forecasting, and causal inference. Underlying technical pillars span machine learning, multi-dimensional data mining, explainable AI, graph models,\u00a0etc.,\u00a0while\u00a0application scenarios can be exemplified by projects like\u00a0<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/project\/spreadsheet-intelligence\/\">Spreadsheet Intelligence<\/a>.\u00a0Our key technologies have been\/are being shipped with Office (Excel, Forms, Word), Power BI & Dynamics, and Bing Search.<\/p><p><b>Visualization and HCI<\/b><\/p><p>We are interested in a variety of research topics in the fields of information visualization, visual analytics, and human-computer interaction.\u00a0By applying machine learning and AI techniques, we\u00a0focus on novel technologies, user interactions, and systems that\u00a0aim to lower the barriers for the users to utilize visualizations\u00a0effectively to enhance their\u00a0data\u00a0analysis and communication\u00a0abilities.\u00a0Specifically,\u00a0we focus on research about\u00a0visualization\/infographics\u00a0design and authoring, data-driven storytelling,\u00a0visual analytics systems, novel user interface for data analysis and exploration,\u00a0data wrangling,\u00a0etc.<\/p><p>\u00a0<\/p><p><b>N<\/b><b>at<\/b><b>ural Language Understanding for Data Science<\/b><\/p><p>Our mission\u00a0is to\u00a0advance natural language understanding\u00a0technologies\u00a0for\u00a0intelligent\u00a0data science.\u00a0First,\u00a0a\u00a0large portion of\u00a0real-world\u00a0data\u00a0is\u00a0unstructured natural language\u00a0data.\u00a0Therefore,\u00a0natural language understanding technologies are required to analyze and understand\u00a0such\u00a0natural language data. Second,\u00a0natural language is the most intuitive and natural interface of a data analysis tool\u00a0that\u00a0allows\u00a0common users\u00a0to\u00a0explore and analyze data\u00a0through\u00a0natural language instructions.\u00a0Specifically,\u00a0we focus on\u00a0research\u00a0topics\u00a0about\u00a0semantic parsing,\u00a0semantic\u00a0role understanding,\u00a0entity recognition,\u00a0dialog,\u00a0etc.\u00a0At the same time,\u00a0we also\u00a0put\u00a0research\u00a0efforts to\u00a0some\u00a0fundamental\u00a0machine learning problems, such as\u00a0compositional generalization capabilities of DNN models, sample efficiency of reinforcement learning, to facilitate\u00a0our\u00a0research on\u00a0natural language understanding.<\/p><p>Our natural language understanding technologies have been shipped\u00a0as an\u00a0Excel\u00a0feature\u00a0(<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" rel=\"noopener noreferrer\" target=\"_blank\" href=\"https:\/\/support.office.com\/en-gb\/article\/ideas-in-excel\">Excel Ideas<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>)\u00a0that allows\u00a0common users\u00a0to analyze Excel tables\u00a0using natural language.\u00a0Collaborating with brother teams, we also have shipped\u00a0our\u00a0technologies to\u00a0PowerBI\u00a0Q&A,\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" rel=\"noopener noreferrer\" target=\"_blank\" href=\"https:\/\/dev.botframework.com\/\">Microsoft\u00a0Bot\u00a0Framework<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, Azure Text Analytics,\u00a0etc.<\/p><p>\u00a0<\/p><p><b>Knowledge Computing<\/b><\/p><p>The\u00a0aim\u00a0of the\u00a0<a href=\"https:\/\/www.microsoft.com\/en-us\/research\/group\/knowledge-computing\/\">Knowledge Computing Group<\/a>\u00a0is to\u00a0build\u00a0machines that can make good use of knowledge to empower every person on the planet to achieve more.\u00a0Natural\u00a0language\u00a0processing,\u00a0information\u00a0extraction,\u00a0table\u00a0interpretation, and\u00a0knowledge\u00a0representation &\u00a0reasoning\u00a0are four\u00a0main focus\u00a0areas.\u00a0Natural\u00a0language\u00a0processing\u00a0(NLP)\u00a0analyzes,\u00a0understands, and\u00a0generates\u00a0languages\u00a0for\u00a0effective and efficient human-machine communication.\u00a0Information extraction\u00a0(IE)\u00a0recognizes\u00a0entity\u00a0mentions,\u00a0mention types,\u00a0named\u00a0entities,\u00a0and\u00a0entity-entity relations\u00a0to create structured data from\u00a0natural\u00a0language\u00a0texts.\u00a0Table interpretation\u00a0(TI)\u00a0detects\u00a0column types, cell\u00a0entities, and\u00a0column-column\u00a0relations to\u00a0facilitate\u00a0question answering over\u00a0tables.\u00a0Knowledge representation & reasoning\u00a0(KRR) provides\u00a0the\u00a0foundation for NLP, IE and TI to represent knowledge symbolically\u00a0and enable automated reasoning\u00a0and computation\u00a0over the representation.<\/p><p>Over the years, we have worked closely with our product team partners at\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" rel=\"noopener noreferrer\" target=\"_blank\" href=\"https:\/\/www.office.com\/\">Office 365<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>,\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" rel=\"noopener noreferrer\" target=\"_blank\" href=\"https:\/\/azure.microsoft.com\/en-us\/services\/cognitive-services\/\">Azure Cognitive Services<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, and\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" rel=\"noopener noreferrer\" target=\"_blank\" href=\"http:\/\/www.bing.com\/\">Bing<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>\u00a0to bring our research results into Microsoft products and services.\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" rel=\"noopener noreferrer\" target=\"_blank\" href=\"https:\/\/techcommunity.microsoft.com\/t5\/microsoft-forms-blog\/design-intelligence-in-microsoft-forms\/ba-p\/257860\">Microsoft Forms Design Intelligence<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>,\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" rel=\"noopener noreferrer\" target=\"_blank\" href=\"https:\/\/support.microsoft.com\/en-us\/office\/create-professional-slide-layouts-with-powerpoint-designer-53c77d7b-dc40-45c2-b684-81415eac0617\">PowerPoint Designer<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>,\u00a0\u00a0<a href=\"https:\/\/www.microsoft.com\/en-us\/microsoft-365\/blog\/2020\/10\/29\/connect-to-your-own-data-with-more-new-data-types-in-excel\/\">Excel Data Types AutoDetect<\/a>,\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" rel=\"noopener noreferrer\" target=\"_blank\" href=\"https:\/\/azure.microsoft.com\/en-us\/services\/cognitive-services\/text-analytics\/\">Azure Text Analytics<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>,\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" rel=\"noopener noreferrer\" target=\"_blank\" href=\"https:\/\/vi.microsoft.com\/en-us\">Microsoft Video Indexer<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>, and\u00a0<a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" rel=\"noopener noreferrer\" target=\"_blank\" href=\"https:\/\/github.com\/Microsoft\/Recognizers-Text\">Microsoft Recognizers Text (open source)<span class=\"sr-only\"> (opens in new tab)<\/span><\/a>\u00a0are just a few recent examples which have incorporated technologies developed by the Knowledge Computing\u00a0group.<\/p><p>\u00a0<\/p><p><b>Software Analytics<\/b><\/p><p>A huge wealth of various data exists in software lifecycle, including source code, feature specifications, bug reports, test cases, execution traces\/logs, and real-world user feedback, etc. Data plays an essential role in modern software development, because hidden in the data is information about the quality of software and services as well as the dynamics of software development. With various analytical and computing technologies, such as pattern recognition, machine learning, data mining, and large-scale data computing & processing, software analytics is to enable software practitioners to perform effective and efficient data exploration and analysis in order to obtain insightful and actionable information for data-driven tasks in engineering software and services.<\/p><p>The mission of the Software Analytics Group at MSR Asia is to advance the state of the art in the software analytics area; and utilize our technologies to help improve the quality of software and services as well as the development productivity for both Microsoft and software industry.<\/p><p>In the past 10 to 15 years, Cloud computing has become the most significant paradigm shift in the IT industry. In this context, in recent years, we have also\u00a0enhanced\u00a0our research on how to innovate AI and ML to solve the problem of Cloud platform, specifically, to use AI\/ML technologies to help effectively and efficiently build and operate highly complex cloud services at scale, which is called Cloud Intelligence. It contains three key pillars: AI for System\/Infrastructure, AI for Customer, and AI for DevOps. Our key technologies have been transferred to multiple Microsoft Cloud services like Azure, Office365, Bing, etc., and significant improvements have been made.<\/p>\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t<\/div>\n\t\n\n\n","protected":false},"excerpt":{"rendered":"<p>Data, Knowledge, and Intelligence (DKI)\u00a0is an interdisciplinary research area with active research in Artificial Intelligence (AI) and Machine Learning, Data Mining and Data Analytics,\u00a0Knowledge Computing,\u00a0NLP,\u00a0information visualization,\u00a0and\u00a0Software Analytics.\u00a0The research in DKI is also grounded as we get data and inspiration from real problems in different domains as well as apply our research results to make real-world impact.<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr_group_start":"","footnotes":""},"research-area":[13556],"msr-group-type":[243694],"msr-locale":[268875],"msr-impact-theme":[],"class_list":["post-714577","msr-group","type-msr-group","status-publish","hentry","msr-research-area-artificial-intelligence","msr-group-type-group","msr-locale-en_us"],"msr_group_start":"","msr_detailed_description":"","msr_further_details":"","msr_hero_images":[],"msr_research_lab":[],"related-researchers":[{"type":"user_nicename","display_name":"Weiwei Cui","user_id":34808,"people_section":"Section name 0","alias":"weiweicu"},{"type":"user_nicename","display_name":"Justin Ding","user_id":32435,"people_section":"Section name 0","alias":"juding"},{"type":"user_nicename","display_name":"Hang Dong","user_id":39687,"people_section":"Section name 0","alias":"hangdong"},{"type":"user_nicename","display_name":"Haoyu Dong","user_id":37128,"people_section":"Section name 0","alias":"hadong"},{"type":"user_nicename","display_name":"Lei Fang","user_id":32635,"people_section":"Section name 0","alias":"leifa"},{"type":"user_nicename","display_name":"Song Ge","user_id":33692,"people_section":"Section name 0","alias":"songge"},{"type":"user_nicename","display_name":"Shi Han","user_id":33618,"people_section":"Section name 0","alias":"shihan"},{"type":"user_nicename","display_name":"Zhitao Hou","user_id":35124,"people_section":"Section name 0","alias":"zhith"},{"type":"user_nicename","display_name":"Danqing Huang","user_id":38724,"people_section":"Section name 0","alias":"dahua"},{"type":"user_nicename","display_name":"Ray Huang","user_id":33358,"people_section":"Section name 0","alias":"rayhuang"},{"type":"user_nicename","display_name":"Yu Kang","user_id":39381,"people_section":"Section name 0","alias":"kay"},{"type":"user_nicename","display_name":"Qingwei Lin \u6797\u5e86\u7ef4","user_id":33318,"people_section":"Section name 0","alias":"qlin"},{"type":"user_nicename","display_name":"Chin-Yew Lin","user_id":31493,"people_section":"Section name 0","alias":"cyl"},{"type":"user_nicename","display_name":"Zeqi Lin","user_id":39751,"people_section":"Section name 0","alias":"zelin"},{"type":"user_nicename","display_name":"Xiao Lv","user_id":37122,"people_section":"Section name 0","alias":"xilv"},{"type":"user_nicename","display_name":"Bo Qiao","user_id":37848,"people_section":"Section name 0","alias":"boqiao"},{"type":"user_nicename","display_name":"Xiaoting Qin","user_id":43008,"people_section":"Section name 0","alias":"xiaotingqin"},{"type":"user_nicename","display_name":"Yun Wang","user_id":37827,"people_section":"Section name 0","alias":"wangyun"},{"type":"user_nicename","display_name":"Fangkai Yang","user_id":41425,"people_section":"Section name 0","alias":"fangkaiyang"},{"type":"user_nicename","display_name":"Dongmei Zhang","user_id":31665,"people_section":"Section name 0","alias":"dongmeiz"},{"type":"user_nicename","display_name":"Haidong Zhang","user_id":31953,"people_section":"Section name 0","alias":"haizhang"},{"type":"user_nicename","display_name":"Pu Zhao","user_id":38886,"people_section":"Section name 0","alias":"puzhao"},{"type":"user_nicename","display_name":"Bin Zhu","user_id":31240,"people_section":"Section name 0","alias":"binzhu"}],"related-publications":[249887,249893,361298,482235,491006,491015,491033,554901,554907,558684,558696,558705,588988,589654,589669,590017,594754,599919,601128,601140,601152,601155,602496,605184,607449,608253,608262,614520,616995,625014,627315,627324,630045,636348,651561,651570,654678,654684,664521,664530,682191,682722,685254,687210,688674,702724,702748,702754,704665,704677,710380,710392,712789,712804,722038,732823,743140,747052,747061,747079,747832,751576,765154,767011,767533,821290,821308,835441,840871,840880,840886,843082,845854,846301,846307,854712,857286,857847,861822,864396,864405,865368,865380,865389,865395,872025,873315,873324,880008,886404,888606,888612,893031,893325,893328,893727,895557,910077,910086,910095,910101,910107,910413,912918,916182,921747,925302,926685,932955,932982,933018,941109,944742,949659,967632,967638,967644,974562,978312,984204,989019,995307,995319,1015500,1015512,1015518,1015527,1016619,1025271,1043472,1049328,1083105,1083138,1094523,1100199,1100211,1100217,1100226,1100241,1101414,1101423,1101438,1134645,1134647,1134649,1134651,1140257,1140259,1145325,1145327,1149271,1155884,1167965,1169496,1169499],"related-downloads":[],"related-videos":[790934],"related-projects":[853323,855579,751528,792599],"related-events":[],"related-opportunities":[],"related-posts":[738559,900798,964185,992625,997686,1004586,1025451,1059168,1085448],"tab-content":[],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group\/714577","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-group"}],"version-history":[{"count":10,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group\/714577\/revisions"}],"predecessor-version":[{"id":1023162,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group\/714577\/revisions\/1023162"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=714577"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=714577"},{"taxonomy":"msr-group-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-group-type?post=714577"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=714577"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=714577"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}