{"id":154173,"date":"2008-08-24T00:00:00","date_gmt":"2008-08-24T00:00:00","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/msr-research-item\/consistent-phrase-relevance-measures\/"},"modified":"2018-10-16T20:24:23","modified_gmt":"2018-10-17T03:24:23","slug":"consistent-phrase-relevance-measures","status":"publish","type":"msr-research-item","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/publication\/consistent-phrase-relevance-measures\/","title":{"rendered":"Consistent Phrase Relevance Measures"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Measuring the relevance between a document and a phrase is fundamental to many information retrieval and matching tasks including on-line advertising. In this paper, we explore two approaches for measuring the relevance between a document and a phrase aiming to provide consistent relevance scores for both in and out-of document phrases. The first approach is a similarity-based method which represents both the document and phrase as term vectors to derive a real-valued relevance score. The second approach takes as input the relevance estimates of some in-document phrases and uses Gaussian Process Regression to predict the score of a target out-of-document phrase. While both of these two approaches work well, the best result is given by a Gaussian Process Regression model, which is significantly better than the similarity-based approach and 10% better than a baseline similarity method using bag-of-word vectors.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Measuring the relevance between a document and a phrase is fundamental to many information retrieval and matching tasks including on-line advertising. In this paper, we explore two approaches for measuring the relevance between a document and a phrase aiming to provide consistent relevance scores for both in and out-of document phrases. The first approach is [&hellip;]<\/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-author-ordering":[{"type":"user_nicename","value":"scottyih"},{"type":"user_nicename","value":"meek"}],"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"Proceedings of The 2nd Annual International Workshop on Data Mining and Audience Intelligence for Advertising (ADKDD-08 Workshop)","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"Proceedings of The 2nd Annual International Workshop on Data Mining and Audience Intelligence for Advertising (ADKDD-08 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