{"id":238235,"date":"2008-06-01T00:00:00","date_gmt":"2008-06-01T07:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/incorporating-string-transformations-in-record-matching\/"},"modified":"2018-10-16T20:03:43","modified_gmt":"2018-10-17T03:03:43","slug":"incorporating-string-transformations-in-record-matching","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/incorporating-string-transformations-in-record-matching\/","title":{"rendered":"Incorporating String Transformations in Record Matching"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Today\u2019s record matching infrastructure does not allow a flexible way to account for synonyms such as \u201cRobert\u201d and \u201cBob\u201d which refer to the same name, and more general forms of string transformations such as abbreviations. We expand the problem of record matching to take such user-defined string transformations as input. These transformations coupled with an underlying similarity function are used to define the similarity between two strings. We demonstrate the effectiveness of this approach via a fuzzy match operation that is used to lookup an input record against a table of records, where we have an additional table of transformations as input. We demonstrate an improvement in record matching quality and efficient retrieval based on our index structure that is cognizant of transformations.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Today\u2019s record matching infrastructure does not allow a flexible way to account for synonyms such as \u201cRobert\u201d and \u201cBob\u201d which refer to the same name, and more general forms of string transformations such as abbreviations. We expand the problem of record matching to take such user-defined string transformations as input. These transformations coupled with an [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13563],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-238235","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-locale-en_us"],"msr_publishername":"ACM - Association for Computing 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