{"id":"https://openalex.org/W4290878070","doi":"https://doi.org/10.1145/3534678.3539304","title":"SagDRE","display_name":"SagDRE","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4290878070","doi":"https://doi.org/10.1145/3534678.3539304"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539304","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534678.3539304","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3534678.3539304","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100619276","display_name":"Ying Wei","orcid":"https://orcid.org/0000-0002-4247-1770"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ying Wei","raw_affiliation_strings":["Iowa State University, Ames, IA, USA"],"affiliations":[{"raw_affiliation_string":"Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100350205","display_name":"Qi Li","orcid":"https://orcid.org/0000-0002-3136-2157"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qi Li","raw_affiliation_strings":["Iowa State University, Ames, IA, USA"],"affiliations":[{"raw_affiliation_string":"Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100619276"],"corresponding_institution_ids":["https://openalex.org/I173911158"],"apc_list":null,"apc_paid":null,"fwci":0.9422,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.76684158,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2000","last_page":"2008"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9998000264167786,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9980000257492065,"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":0.8339627385139465},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.7481623888015747},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.6209763288497925},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6064349412918091},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5716829895973206},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5609365105628967},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5554465055465698},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.514719545841217},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4904336631298065},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.48187050223350525},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.47633105516433716},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44345778226852417},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.42445671558380127},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.41231662034988403},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2719796299934387},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2505761384963989},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20339909195899963}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8339627385139465},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.7481623888015747},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.6209763288497925},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6064349412918091},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5716829895973206},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5609365105628967},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5554465055465698},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.514719545841217},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4904336631298065},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.48187050223350525},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.47633105516433716},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44345778226852417},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.42445671558380127},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.41231662034988403},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2719796299934387},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2505761384963989},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20339909195899963},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3534678.3539304","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534678.3539304","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3534678.3539304","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534678.3539304","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6000000238418579,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G3467354657","display_name":null,"funder_award_id":"IIS-2007941","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6761533590","display_name":null,"funder_award_id":"2022-67015-36217","funder_id":"https://openalex.org/F4320332299","funder_display_name":"National Institute of Food and Agriculture"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332299","display_name":"National Institute of Food and Agriculture","ror":"https://ror.org/05qx3fv49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2138806274","https://openalex.org/W2250539671","https://openalex.org/W2398936787","https://openalex.org/W2599674900","https://openalex.org/W2610930722","https://openalex.org/W2736196485","https://openalex.org/W2737608545","https://openalex.org/W2897782208","https://openalex.org/W2952179106","https://openalex.org/W2952768212","https://openalex.org/W2962902328","https://openalex.org/W2963014179","https://openalex.org/W2963020213","https://openalex.org/W2963241825","https://openalex.org/W2963655104","https://openalex.org/W2963899396","https://openalex.org/W2970771982","https://openalex.org/W2971221499","https://openalex.org/W2990385600","https://openalex.org/W2996284762","https://openalex.org/W3021224558","https://openalex.org/W3035053871","https://openalex.org/W3044057088","https://openalex.org/W3093872895","https://openalex.org/W3093891978","https://openalex.org/W3102663935","https://openalex.org/W3103836967","https://openalex.org/W3114962796","https://openalex.org/W3118018449"],"related_works":["https://openalex.org/W842810586","https://openalex.org/W4319940250","https://openalex.org/W2352298027","https://openalex.org/W2092919065","https://openalex.org/W3138801416","https://openalex.org/W4236762297","https://openalex.org/W2444550338","https://openalex.org/W2169232658","https://openalex.org/W2369351710","https://openalex.org/W2594363579"],"abstract_inverted_index":{"Relation":[0],"extraction":[1,15],"(RE)":[2],"is":[3],"an":[4,117,141],"important":[5],"task":[6,16],"for":[7,140],"many":[8,27],"natural":[9],"language":[10],"processing":[11],"applications.":[12],"Document-level":[13],"relation":[14],"aims":[17,154],"to":[18,29,57,88,102,110,121,155],"extract":[19],"the":[20,30,45,54,74,79,90,94,98,104,111,123,172,175],"relations":[21,42,133],"within":[22],"a":[23,138,147],"document":[24,95,139],"and":[25,39,72,96,144,160],"poses":[26],"challenges":[28],"RE":[31,51,129],"tasks":[32],"as":[33],"it":[34],"requires":[35],"reasoning":[36],"across":[37],"sentences":[38],"handling":[40],"multiple":[41,132],"expressed":[43,136],"in":[44,93,137],"same":[46],"document.":[47],"Existing":[48],"state-of-the-art":[49],"document-level":[50,128],"models":[52],"use":[53],"graph":[55],"structure":[56],"better":[58],"connect":[59],"long-distance":[60],"correlations.":[61],"In":[62,113],"this":[63],"work,":[64],"we":[65,115],"propose":[66,116],"SagDRE":[67],"model,":[68],"which":[69],"further":[70],"considers":[71],"captures":[73],"original":[75],"sequential":[76,100],"information":[77,91,101],"from":[78,107,168],"text.":[80],"The":[81,151,163],"proposed":[82,176],"model":[83],"learns":[84],"sentence-level":[85],"directional":[86],"edges":[87],"capture":[89],"flow":[92],"uses":[97],"token-level":[99],"encode":[103],"shortest":[105],"paths":[106],"one":[108],"entity":[109,142],"other.":[112],"addition,":[114],"adaptive":[118],"margin":[119],"loss":[120,152],"address":[122],"long-tailed":[124],"multi-label":[125],"problem":[126],"of":[127,174],"tasks,":[130],"where":[131],"can":[134],"be":[135],"pair":[143],"there":[145],"are":[146],"few":[148],"popular":[149],"relations.":[150],"function":[153],"encourage":[156],"separations":[157],"between":[158],"positive":[159],"negative":[161],"classes.":[162],"experimental":[164],"results":[165],"on":[166],"datasets":[167],"various":[169],"domains":[170],"demonstrate":[171],"effectiveness":[173],"methods.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2022-08-12T00:00:00"}