Web search engines like Bing and Google have amassed a tremendous amount of data assets. These include query-click logs, web crawl corpus, an entity knowledge graph and geographic\/maps data. In the Data Management, Exploration and Mining (DMX) group at Microsoft Research, we investigate ways to mine the above data assets to derive new data that can provide new value to a wide variety of applications. We expose the new data as cloud data services that can be consumed by Microsoft products and services as well as third party applications. We describe two such data services we have built over the past few years: synonym service and web table service. These two data services have shipped in several Microsoft products and services including Bing, Office 365, Cortana, Bing synonyms API and Bing Knowledge API.<\/p>\n","protected":false},"excerpt":{"rendered":"
Web search engines like Bing and Google have amassed a tremendous amount of data assets. These include query-click logs, web crawl corpus, an entity knowledge graph and geographic\/maps data. In the Data Management, Exploration and Mining (DMX) group at Microsoft Research, we investigate ways to mine the above data assets to derive new data that […]<\/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":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13563,13555],"msr-publication-type":[193715],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-357899","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-research-area-search-information-retrieval","msr-locale-en_us"],"msr_publishername":"IEEE","msr_edition":"","msr_affiliation":"","msr_published_date":"2016-09-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"Bulletin of the IEEE Computer Society Technical Committee on Data Engineering","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"357902","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"dataservices","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2017\/01\/dataservices.pdf","id":357902,"label_id":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"user_nicename","value":"kaushik","user_id":32503,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=kaushik"},{"type":"user_nicename","value":"surajitc","user_id":33764,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=surajitc"},{"type":"user_nicename","value":"zmchen","user_id":35150,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=zmchen"},{"type":"user_nicename","value":"krisgan","user_id":32579,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=krisgan"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[171259,171092],"publication":[],"video":[],"download":[],"msr_publication_type":"article","related_content":{"projects":[{"ID":171259,"post_title":"Synonym Mining","post_name":"synonym-mining","post_type":"msr-project","post_date":"2014-01-07 17:35:54","post_modified":"2018-07-19 11:58:46","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/synonym-mining\/","post_excerpt":"The same entity is often referred to in a variety of ways. For example, the camera Canon 600d is also referred to as \"canon rebel t3i\", the celebrity Jennifer Lopez is also referred to as \"jlo\" and Seattle Tacoma International Airport is also referred to as \"sea tac\". These are known as synonyms. Without knowledge of synonyms, many applications like e-commerce search will fail to return relevant results. We leverage the data assets amassed by…","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171259"}]}},{"ID":171092,"post_title":"Web Data Extraction and Search","post_name":"structured-data-search","post_type":"msr-project","post_date":"2013-02-09 02:53:21","post_modified":"2019-08-19 18:23:22","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/structured-data-search\/","post_excerpt":"The goal of this project is to extract structured data on the web (like html tables, lists, spreadsheets etc.) and make it accessible\/searchable on\u00a0Bing and Office 365. Some of the technical challenges: Table classification and understanding: The vast majority of html tables are used for formatting\/layout purposes; they do not any contain useful content . How do we automatically filter out such tables? 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