{"id":"https://openalex.org/W4379365396","doi":"https://doi.org/10.1145/3583788.3583804","title":"LDRC: Long-tail Distantly Supervised Relation Extraction via Contrastive Learning","display_name":"LDRC: Long-tail Distantly Supervised Relation Extraction via Contrastive Learning","publication_year":2023,"publication_date":"2023-01-05","ids":{"openalex":"https://openalex.org/W4379365396","doi":"https://doi.org/10.1145/3583788.3583804"},"language":"en","primary_location":{"id":"doi:10.1145/3583788.3583804","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583788.3583804","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 The 7th International Conference on Machine Learning and Soft Computing (ICMLSC)","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/A5101527276","display_name":"Tingwei Li","orcid":"https://orcid.org/0000-0003-2122-3134"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tingwei Li","raw_affiliation_strings":["State Key Laboratory of Networking &amp; Switching Technology, Beijing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0003-2122-3134","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking &amp; Switching Technology, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhi Wang","orcid":"https://orcid.org/0000-0002-0299-3996"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Wang","raw_affiliation_strings":["State Key Laboratory of Networking &amp; Switching Technology, Beijing University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-0299-3996","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking &amp; Switching Technology, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101527276"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.5112,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70297201,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"110","last_page":"117"},"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":0.9991000294685364,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9955000281333923,"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/relationship-extraction","display_name":"Relationship extraction","score":0.7947505712509155},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.7156776785850525},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6575236320495605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6363252997398376},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5296661257743835},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4517750144004822},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4476166367530823},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.4328044652938843},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32629847526550293},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21906998753547668},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.21129664778709412},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.08180153369903564}],"concepts":[{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.7947505712509155},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.7156776785850525},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6575236320495605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6363252997398376},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5296661257743835},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4517750144004822},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4476166367530823},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.4328044652938843},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32629847526550293},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21906998753547668},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.21129664778709412},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.08180153369903564},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583788.3583804","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3583788.3583804","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 The 7th International Conference on Machine Learning and Soft Computing (ICMLSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2094728533","https://openalex.org/W2251135946","https://openalex.org/W2515462165","https://openalex.org/W2559188277","https://openalex.org/W2887428522","https://openalex.org/W2892181857","https://openalex.org/W2896457183","https://openalex.org/W2919278763","https://openalex.org/W2963912690","https://openalex.org/W2964022985","https://openalex.org/W2971296908","https://openalex.org/W3156636935","https://openalex.org/W3174244822","https://openalex.org/W4237040408","https://openalex.org/W4287890475","https://openalex.org/W4289123106","https://openalex.org/W4365799947"],"related_works":["https://openalex.org/W2528512298","https://openalex.org/W2368651715","https://openalex.org/W2096954272","https://openalex.org/W3201556757","https://openalex.org/W1515542156","https://openalex.org/W3002472320","https://openalex.org/W2962764947","https://openalex.org/W2947903144","https://openalex.org/W2993873509","https://openalex.org/W2766478297"],"abstract_inverted_index":{"Long-tail":[0],"problem":[1,19],"is":[2,71,90],"one":[3],"of":[4],"the":[5,17,46,64,93,98,117],"major":[6],"challenges":[7],"in":[8],"distantly":[9],"supervised":[10],"relation":[11,37,85,107],"extraction.":[12,108],"Some":[13],"recent":[14],"works":[15],"on":[16,45,122],"long-tail":[18,49,69,106],"attempt":[20],"to":[21,31,67,95,104],"transfer":[22],"knowledge":[23],"from":[24],"data-rich":[25],"and":[26,50,63,87],"semantically":[27],"similar":[28],"head":[29,51],"classes":[30,34],"data-poor":[32],"tail":[33],"using":[35],"a":[36,54,78],"hierarchical":[38],"tree.":[39],"These":[40],"methods,":[41],"however,":[42],"are":[43],"based":[44],"assumption":[47],"that":[48,83,112],"relations":[52,70],"have":[53],"strong":[55],"correlation,":[56],"which":[57],"does":[58],"not":[59,73],"always":[60],"hold":[61],"true,":[62],"model\u2019s":[65],"ability":[66],"learn":[68,97],"essentially":[72],"improved.":[74],"In":[75],"this":[76],"paper,":[77],"novel":[79],"joint":[80],"learning":[81,89],"framework":[82],"combines":[84],"extraction":[86],"contrastive":[88],"proposed,":[91],"allowing":[92],"model":[94,115,121],"directly":[96],"subtle":[99],"differences":[100],"between":[101],"different":[102],"categories":[103],"improve":[105],"Experimental":[109],"results":[110],"show":[111],"our":[113],"proposed":[114],"outperforms":[116],"current":[118],"state-of-the-art":[119],"(SOTA)":[120],"various":[123],"mainstream":[124],"datasets.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
