{"id":152681,"date":"2003-04-01T00:00:00","date_gmt":"2003-04-01T00:00:00","guid":{"rendered":"https:\/\/new-cm-edgedigital.pages.dev\/en-us\/research\/msr-research-item\/learning-and-exploiting-non-consecutive-string-patterns-for-information-extraction\/"},"modified":"2018-10-16T20:09:56","modified_gmt":"2018-10-17T03:09:56","slug":"learning-and-exploiting-non-consecutive-string-patterns-for-information-extraction","status":"publish","type":"msr-research-item","link":"https:\/\/new-cm-edgedigital.pages.dev\/en-us\/research\/publication\/learning-and-exploiting-non-consecutive-string-patterns-for-information-extraction\/","title":{"rendered":"Learning and Exploiting Non-Consecutive String Patterns for Information Extraction"},"content":{"rendered":"<div class=\"asset-content\">\n<p>This paper is concerned with the problem of learning and exploiting string patterns in natural language processing, particularly information extraction. We propose a new algorithm for learning such patterns. Our algorithm is novel in that it can learn non-consecutive patterns with constraints , which are necessary for information extraction. Specifically, it employs an extended version of the so-called apriori algorithm at the pattern generation step. Our experimental results indicate that in information extraction the use of non-consecutive patterns with constraints is significantly better than the use of only consecutive patterns.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper is concerned with the problem of learning and exploiting string patterns in natural language processing, particularly information extraction. We propose a new algorithm for learning such patterns. Our algorithm is novel in that it can learn non-consecutive patterns with constraints , which are necessary for information extraction. Specifically, it employs an extended version [&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":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"MSR-TR-2003-33","msr_organization":"","msr_pages_string":"8","msr_page_range_start":"8","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"Shenjie Li","msr_other_contributors":"","msr_speaker":"","msr_award":"","msr_affiliation":"","msr_institution":"Microsoft 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