{"id":"https://openalex.org/W4416251966","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228163","title":"CSF-DSRE:A Distantly Supervised Relation Extraction Model Based on Contextual Semantic Fusion","display_name":"CSF-DSRE:A Distantly Supervised Relation Extraction Model Based on Contextual Semantic Fusion","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251966","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228163"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5100400712","display_name":"Min Li","orcid":"https://orcid.org/0000-0001-9013-2020"},"institutions":[{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Min Li","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China"],"affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101282093","display_name":"Juan Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juan Yu","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China"],"affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066041146","display_name":"Mingle Zhou","orcid":"https://orcid.org/0000-0003-4911-276X"},"institutions":[{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingle Zhou","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China"],"affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024716590","display_name":"Jiachen Li","orcid":"https://orcid.org/0000-0002-3543-6088"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiachen Li","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China"],"affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024839815","display_name":"Delong Han","orcid":"https://orcid.org/0000-0001-7195-3413"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Delong Han","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China"],"affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan),Jinan,China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100400712"],"corresponding_institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18310246,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9153000116348267,"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":0.9153000116348267,"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":0.03370000049471855,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.008799999952316284,"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/relation","display_name":"Relation (database)","score":0.6948999762535095},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5496000051498413},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.5375000238418579},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48840001225471497},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4799000024795532},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4629000127315521},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.45410001277923584},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4291999936103821},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.41769999265670776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7652000188827515},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6948999762535095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6468999981880188},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5496000051498413},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.5375000238418579},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.51910001039505},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48840001225471497},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4799000024795532},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4629000127315521},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.45410001277923584},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4291999936103821},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4219000041484833},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.41769999265670776},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.39410001039505005},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.335099995136261},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.33469998836517334},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.26660001277923584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228163","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1604644367","https://openalex.org/W2107598941","https://openalex.org/W2154851992","https://openalex.org/W2251135946","https://openalex.org/W2515462165","https://openalex.org/W2759211898","https://openalex.org/W2759996146","https://openalex.org/W2765245454","https://openalex.org/W2785105945","https://openalex.org/W2891417293","https://openalex.org/W2952402849","https://openalex.org/W2963912736","https://openalex.org/W2990156802","https://openalex.org/W3153655254","https://openalex.org/W3174244822","https://openalex.org/W3175518369","https://openalex.org/W4221150603","https://openalex.org/W4285169918","https://openalex.org/W4386848090","https://openalex.org/W4386863976","https://openalex.org/W4402352515"],"related_works":[],"abstract_inverted_index":{"In":[0,89],"the":[1,15,20,27,52,63,66,76,94,106,109,115,126,141,151,157,173,195],"Distantly":[2],"Supervised":[3],"Relation":[4],"Extraction":[5],"(DSRE)":[6],"task,":[7],"it":[8,33],"is":[9,190],"typically":[10],"assumed":[11],"that":[12,73,203],"sentences":[13,50],"containing":[14],"same":[16,21],"entity":[17,110,198],"pair":[18],"reflect":[19],"relation.":[22],"While":[23],"this":[24,90],"assumption":[25],"simplifies":[26],"learning":[28],"process":[29],"to":[30,54,104,122,135,149,171,192],"some":[31],"extent,":[32],"inevitably":[34],"introduces":[35],"substantial":[36],"noise.":[37],"Previous":[38],"extensive":[39],"research":[40],"has":[41,59],"utilized":[42],"a":[43,79,166],"series":[44],"of":[45,153,168],"selective":[46],"attention":[47],"mechanisms":[48],"on":[49,177],"in":[51,82,114,175],"bag":[53],"extract":[55],"relation":[56,83,183],"features,":[57,180],"but":[58],"seldom":[60],"considered":[61],"leveraging":[62],"information":[64,142],"surrounding":[65,75],"entities":[67,77],"and":[68,111,145,164],"different":[69,120,147],"features.":[70],"We":[71],"argue":[72],"tokens":[74,113],"play":[78],"significant":[80,207],"role":[81],"classification,":[84],"though":[85],"their":[86],"importance":[87,121],"varies.":[88],"paper,":[91],"we":[92],"propose":[93],"Dynamic":[95],"Semantic":[96],"Interaction":[97],"(DSI)":[98],"module,":[99],"which":[100],"uses":[101,132],"token-level":[102],"features":[103,148],"calculate":[105,136],"similarity":[107],"between":[108,197],"other":[112],"sentence":[116],"as":[117],"weights,":[118],"assigning":[119],"each":[123],"token.":[124],"Additionally,":[125],"Responsiveness":[127],"Feature":[128],"Fusion":[129],"Strategy":[130],"(RFFS)":[131],"Euclidean":[133],"distance":[134],"reliability":[137],"scores,":[138],"adaptively":[139],"adjusts":[140],"fusion":[143],"process,":[144],"weights":[146],"reduce":[150],"impact":[152],"noisy":[154],"information.":[155],"Finally,":[156],"Relation-Aware":[158],"Contextual":[159],"Modeling":[160],"(RACM)":[161],"module":[162],"initializes":[163],"trains":[165],"set":[167],"seed":[169],"vectors":[170],"guide":[172],"model":[174,189,205],"focusing":[176],"relation-relevant":[178],"contextual":[179],"thereby":[181],"improving":[182],"recognition.":[184],"Combining":[185],"these":[186],"methods,":[187],"our":[188,204],"able":[191],"better":[193],"predict":[194],"relations":[196],"pairs.":[199],"Experimental":[200],"results":[201],"show":[202],"demonstrates":[206],"advantages":[208],"across":[209],"various":[210],"mainstream":[211],"DSRE":[212],"datasets.":[213]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-14T00:00:00"}