{"id":"https://openalex.org/W3037295084","doi":"https://doi.org/10.18653/v1/2020.bionlp-1.4","title":"Improving Biomedical Analogical Retrieval with Embedding of Structural Dependencies","display_name":"Improving Biomedical Analogical Retrieval with Embedding of Structural Dependencies","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3037295084","doi":"https://doi.org/10.18653/v1/2020.bionlp-1.4","mag":"3037295084"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2020.bionlp-1.4","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.bionlp-1.4","pdf_url":"https://www.aclweb.org/anthology/2020.bionlp-1.4.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/2020.bionlp-1.4.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020738607","display_name":"Amandalynne Paullada","orcid":"https://orcid.org/0000-0002-9585-0125"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amandalynne Paullada","raw_affiliation_strings":["Department of Linguistics, University of Washington, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Linguistics, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032838430","display_name":"Bethany Percha","orcid":"https://orcid.org/0000-0003-0988-4183"},"institutions":[{"id":"https://openalex.org/I4210147155","display_name":"Pediatrics and Genetics","ror":"https://ror.org/03t432d20","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210147155"]},{"id":"https://openalex.org/I98704320","display_name":"Icahn School of Medicine at Mount Sinai","ror":"https://ror.org/04a9tmd77","country_code":"US","type":"education","lineage":["https://openalex.org/I1320796813","https://openalex.org/I98704320"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bethany Percha","raw_affiliation_strings":["Dept. of Medicine and Dept. of Genetics & Genomic Sciences,","Icahn School of Medicine at Mount Sinai, New York, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Medicine and Dept. of Genetics & Genomic Sciences,","institution_ids":["https://openalex.org/I4210147155"]},{"raw_affiliation_string":"Icahn School of Medicine at Mount Sinai, New York, NY, USA","institution_ids":["https://openalex.org/I98704320"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071178113","display_name":"Trevor Cohen","orcid":"https://orcid.org/0000-0003-0159-6697"},"institutions":[{"id":"https://openalex.org/I2801852214","display_name":"University of Washington Medical Center","ror":"https://ror.org/00wbzw723","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I2801852214"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Trevor Cohen","raw_affiliation_strings":["Dept. of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I2801852214"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8125,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.78948473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"38","last_page":"48"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9977999925613403,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9977999925613403,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9933000206947327,"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":0.8023891448974609},{"id":"https://openalex.org/keywords/analogy","display_name":"Analogy","score":0.7653211355209351},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.746481716632843},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.718405544757843},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.634213924407959},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5921952128410339},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5676896572113037},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5485799908638},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5420300960540771},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5382418632507324},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.5333229303359985},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.4745646119117737},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08488166332244873},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08211061358451843}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8023891448974609},{"id":"https://openalex.org/C521332185","wikidata":"https://www.wikidata.org/wiki/Q185816","display_name":"Analogy","level":2,"score":0.7653211355209351},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.746481716632843},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.718405544757843},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.634213924407959},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5921952128410339},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5676896572113037},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5485799908638},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5420300960540771},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5382418632507324},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.5333229303359985},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.4745646119117737},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08488166332244873},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08211061358451843},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2020.bionlp-1.4","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.bionlp-1.4","pdf_url":"https://www.aclweb.org/anthology/2020.bionlp-1.4.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2020.bionlp-1.4","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.bionlp-1.4","pdf_url":"https://www.aclweb.org/anthology/2020.bionlp-1.4.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8399999737739563,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G3259504913","display_name":null,"funder_award_id":"R01 LM011563","funder_id":"https://openalex.org/F4320337372","funder_display_name":"U.S. National Library of Medicine"}],"funders":[{"id":"https://openalex.org/F4320337372","display_name":"U.S. National Library of Medicine","ror":"https://ror.org/0060t0j89"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3037295084.pdf","grobid_xml":"https://content.openalex.org/works/W3037295084.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W24493708","https://openalex.org/W1486990335","https://openalex.org/W1577542843","https://openalex.org/W1614298861","https://openalex.org/W1615991656","https://openalex.org/W1662133657","https://openalex.org/W1964670939","https://openalex.org/W1989277387","https://openalex.org/W2011726136","https://openalex.org/W2039336675","https://openalex.org/W2063280109","https://openalex.org/W2076766778","https://openalex.org/W2094061585","https://openalex.org/W2099307202","https://openalex.org/W2119412782","https://openalex.org/W2141599568","https://openalex.org/W2145578524","https://openalex.org/W2156689959","https://openalex.org/W2157542201","https://openalex.org/W2250189634","https://openalex.org/W2251771443","https://openalex.org/W2460442863","https://openalex.org/W2592493346","https://openalex.org/W2766208765","https://openalex.org/W2767891136","https://openalex.org/W2781816753","https://openalex.org/W2795129839","https://openalex.org/W2803986565","https://openalex.org/W2841315182","https://openalex.org/W2888329843","https://openalex.org/W2899142323","https://openalex.org/W2906838744","https://openalex.org/W2912324667","https://openalex.org/W2950339735","https://openalex.org/W2963176474","https://openalex.org/W2963491049","https://openalex.org/W2971987084","https://openalex.org/W2987928072","https://openalex.org/W3026528364","https://openalex.org/W4233698560","https://openalex.org/W4241881032","https://openalex.org/W4248234957"],"related_works":["https://openalex.org/W2372020181","https://openalex.org/W2156531654","https://openalex.org/W1581723585","https://openalex.org/W4378714697","https://openalex.org/W2294330161","https://openalex.org/W2940472653","https://openalex.org/W2253069048","https://openalex.org/W2804553224","https://openalex.org/W140709781","https://openalex.org/W3214340375"],"abstract_inverted_index":{"Inferring":[0],"the":[1,4,17,58,72],"nature":[2],"of":[3,19,65,74,87,121,139,156,168],"relationships":[5,60,97,118,141],"between":[6,119],"biomedical":[7,96,140,171],"entities":[8,122],"from":[9],"text":[10],"is":[11],"an":[12,35],"important":[13],"problem":[14],"due":[15],"to":[16,38,56,62,94,115,130],"difficulty":[18],"maintaining":[20],"human-curated":[21],"knowledge":[22],"bases":[23],"in":[24,53,78,81,98,124,148],"rapidly":[25],"evolving":[26],"fields.":[27],"Neural":[28],"word":[29,43,79],"embeddings":[30,80,162],"have":[31],"earned":[32],"attention":[33],"for":[34,170],"apparent":[36],"ability":[37,55],"encode":[39,57],"relational":[40],"information.":[41],"However,":[42],"embedding":[44],"models":[45],"that":[46],"disregard":[47],"syntax":[48],"during":[49],"training":[50],"are":[51,167],"limited":[52],"their":[54],"structural":[59],"fundamental":[61],"cognitive":[63],"theories":[64],"analogy.":[66],"In":[67],"this":[68],"paper,":[69],"we":[70,84],"demonstrate":[71],"utility":[73],"encoding":[75,163],"dependency":[76,164],"structure":[77],"a":[82,92,103,109],"model":[83,129],"call":[85],"Embedding":[86],"Structural":[88],"Dependencies":[89],"(ESD)":[90],"as":[91,142],"way":[93],"represent":[95],"two":[99],"analogical":[100],"retrieval":[101,105],"tasks:":[102],"relationship":[104],"(RR)":[106,155],"task,":[107],"and":[108,153],"literature-based":[110],"discovery":[111],"(LBD)":[112,152],"task":[113],"meant":[114],"hypothesize":[116],"plausible":[117],"pairs":[120],"unseen":[123],"training.":[125],"We":[126],"compare":[127],"our":[128,143],"skipgram":[131],"with":[132,146],"negative":[133],"sampling":[134],"(SGNS),":[135],"using":[136],"19":[137],"databases":[138],"evaluation":[144],"data,":[145],"improvements":[147],"performance":[149],"on":[150],"17":[151],"18":[154],"these":[157],"sets.":[158],"These":[159],"results":[160],"suggest":[161],"path":[165],"information":[166],"value":[169],"analogy":[172],"retrieval.":[173]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}