{"id":"https://openalex.org/W2500040412","doi":"https://doi.org/10.1145/2851613.2851866","title":"A method for obtaining rich data from PubMed using SVM","display_name":"A method for obtaining rich data from PubMed using SVM","publication_year":2016,"publication_date":"2016-04-04","ids":{"openalex":"https://openalex.org/W2500040412","doi":"https://doi.org/10.1145/2851613.2851866","mag":"2500040412"},"language":"en","primary_location":{"id":"doi:10.1145/2851613.2851866","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2851613.2851866","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028729111","display_name":"Junbum Cha","orcid":"https://orcid.org/0000-0001-8248-3138"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Junbum Cha","raw_affiliation_strings":["Yonsei University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101860937","display_name":"Jeongwoo Kim","orcid":"https://orcid.org/0000-0001-9417-536X"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jeongwoo Kim","raw_affiliation_strings":["Yonsei University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089434512","display_name":"Yunku Yeu","orcid":"https://orcid.org/0000-0001-7544-531X"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yunku Yeu","raw_affiliation_strings":["Yonsei University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100322270","display_name":"Sanghyun Park","orcid":"https://orcid.org/0000-0002-5196-6193"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sanghyun Park","raw_affiliation_strings":["Yonsei University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Yonsei University, Seoul, Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5028729111"],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":0.1667,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.63159047,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"37","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7393999695777893},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6697300672531128},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5746322870254517},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5644530057907104},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5484904646873474},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5396630167961121},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5269946455955505},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21378901600837708},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11883392930030823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7393999695777893},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6697300672531128},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5746322870254517},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5644530057907104},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5484904646873474},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5396630167961121},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5269946455955505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21378901600837708},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11883392930030823},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2851613.2851866","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2851613.2851866","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.44999998807907104,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G4887354043","display_name":null,"funder_award_id":"NRF-2015R1A2A1A05001845","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2071427873","https://openalex.org/W2131904035","https://openalex.org/W2142995543","https://openalex.org/W2159482845","https://openalex.org/W2949547296","https://openalex.org/W4383905842"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W42295635","https://openalex.org/W2530420969","https://openalex.org/W2051187167"],"abstract_inverted_index":{"As":[0],"text":[1,12,17,60],"mining":[2],"advances":[3],"rapidly":[4],"in":[5,29,62],"the":[6,9,41],"biomedical":[7],"field,":[8],"importance":[10],"of":[11,35],"data":[13,18,37,42,61],"is":[14,19,38,43],"increasing.":[15],"Most":[16],"obtained":[20,66],"through":[21],"a":[22,32,55,68],"Medical":[23],"Subjects":[24],"Headings":[25],"(MeSH)":[26],"term":[27,71],"search;":[28],"this":[30,51],"process,":[31],"large":[33],"amount":[34],"valuable":[36],"missed":[39],"because":[40],"not":[44],"indexed":[45],"yet":[46],"with":[47],"MeSH":[48,70],"terms.":[49],"In":[50],"paper,":[52],"we":[53],"propose":[54],"method":[56],"for":[57],"obtaining":[58],"additional":[59],"addition":[63],"to":[64],"that":[65],"using":[67],"conventional":[69],"search.":[72]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
