000002300 001__ 2300
000002300 005__ 20250424232723.0
000002300 0247_ $$2DOI$$a10.6083/M4CV4G05
000002300 037__ $$aETD
000002300 245__ $$aUsing symbolic network logical analysis as a knowledge extraction method on Medline abstracts
000002300 260__ $$bOregon Health and Science University
000002300 269__ $$a2004
000002300 336__ $$aThesis
000002300 502__ $$bM.S.
000002300 520__ $$aThe bibliome of biomedical literature is already too large and growing much too rapidly for researchers to stay current on all information relevant to their work. Text mining and knowledge extraction can assist researchers by analyzing bibliographic databases as a whole and extracting knowledge by connecting information between multiple records. Symbolic network logistical analysis -- a novel text mining method based on analyzing the network structure created by symbol occurrences -- was developed as a way to extend the capabilities of knowledge extraction.
000002300 540__ $$fCC BY
000002300 542__ $$fIn copyright - single owner
000002300 650__ $$aInformation Storage and Retrieval$$028998
000002300 650__ $$aMEDLINE$$028990
000002300 650__ $$aMedical Informatics$$021938
000002300 650__ $$aDatabases, Bibliographic$$028963
000002300 650__ $$aData Mining$$038911
000002300 691__ $$aSchool of Medicine$$041369
000002300 692__ $$aDepartment of Medical Informatics and Clinical Epidemiology$$041422
000002300 7001_ $$aCohen, Aaron$$uOregon Health and Science University$$041354
000002300 8564_ $$9898e3dd6-695a-4df0-93eb-9127a438463b$$s19666390$$uhttps://digitalcollections.ohsu.edu/record/2300/files/3031_etd.pdf$$ePublic$$2f4b42beec84450b8e2b62490edba55ce$$31
000002300 905__ $$a/rest/prod/79/40/7x/35/79407x355
000002300 909CO $$ooai:digitalcollections.ohsu.edu:2300$$pstudent-work
000002300 980__ $$aBiomedical Informatics