{"id":"https://openalex.org/W4411015051","doi":"https://doi.org/10.1145/3728725.3728736","title":"ColKGC: Collaborative Enhancement using Large Language Model for Knowledge Graph Completion","display_name":"ColKGC: Collaborative Enhancement using Large Language Model for Knowledge Graph Completion","publication_year":2025,"publication_date":"2025-02-21","ids":{"openalex":"https://openalex.org/W4411015051","doi":"https://doi.org/10.1145/3728725.3728736"},"language":"en","primary_location":{"id":"doi:10.1145/3728725.3728736","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728736","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728736","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 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728736","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5117824836","display_name":"Heng Fang","orcid":"https://orcid.org/0009-0008-0497-4677"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Heng Fang","raw_affiliation_strings":["Anhui University, School of Computer Science and Technology, Hefei, Anhui, China"],"raw_orcid":"https://orcid.org/0009-0008-0497-4677","affiliations":[{"raw_affiliation_string":"Anhui University, School of Computer Science and Technology, Hefei, Anhui, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5117824836"],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05641258,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"66","last_page":"71"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9933000206947327,"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"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7648189067840576},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5846496224403381},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4743986129760742},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.28473952412605286},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27376681566238403}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7648189067840576},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5846496224403381},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4743986129760742},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28473952412605286},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27376681566238403}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3728725.3728736","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728736","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728736","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 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3728725.3728736","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728736","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728736","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 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8186043198","display_name":null,"funder_award_id":"62376001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321435","display_name":"Anhui University","ror":"https://ror.org/05th6yx34"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411015051.pdf","grobid_xml":"https://content.openalex.org/works/W4411015051.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W2148437670","https://openalex.org/W2250184916","https://openalex.org/W2432356473","https://openalex.org/W2607380417","https://openalex.org/W2728059831","https://openalex.org/W3117339789","https://openalex.org/W3130909864","https://openalex.org/W3155001903","https://openalex.org/W4225412853","https://openalex.org/W4226142803","https://openalex.org/W4320854389","https://openalex.org/W4385572435","https://openalex.org/W4390512419","https://openalex.org/W4390692489","https://openalex.org/W4396757564","https://openalex.org/W4401754921","https://openalex.org/W6718112784"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Knowledge":[0,10],"Graph":[1],"Completion":[2],"(KGC)":[3],"aims":[4],"to":[5,26,67,105,144,185],"address":[6],"incomplete":[7],"facts":[8],"in":[9,23,32,219,227],"Graphs":[11],"(KGs).":[12],"As":[13],"a":[14],"mainstream":[15],"approach":[16],"for":[17,65,97],"KGC,":[18],"text-based":[19,77,111,153,167],"methods":[20,78],"are":[21],"limited":[22],"performance":[24],"due":[25],"insufficient":[27],"knowledge":[28,58,80,83,119,149,209],"caused":[29],"by":[30,136,151],"constraints":[31],"fine-tuning":[33,134],"data.":[34],"To":[35,72],"incorporate":[36],"broader":[37],"external":[38,87],"knowledge,":[39,61,88],"some":[40],"researchers":[41],"explored":[42],"KGC":[43,70,98,196],"approaches":[44],"based":[45],"on":[46,79,86],"large":[47],"language":[48],"models":[49],"(LLMs),":[50],"but":[51],"general-purpose":[52],"LLMs":[53,85,143,229],"lack":[54],"direct":[55],"awareness":[56],"of":[57,76,141,178,194],"graph":[59,81,120,147,210],"domain":[60,82,148],"making":[62],"it":[63],"challenging":[64],"them":[66],"independently":[68],"perform":[69],"tasks.":[71],"balance":[73],"the":[74,102,107,110,114,118,127,133,139,142,146,152,161,166,171,175,179,183,187,191,195,223],"dependence":[75],"and":[84,113,116,173,222],"we":[89,131,159],"propose":[90],"Collaborative":[91],"Enhancement":[92],"using":[93],"Large":[94],"Language":[95],"Model":[96],"(ColKGC).":[99],"We":[100],"define":[101],"prompt":[103,172],"template":[104],"implement":[106],"interaction":[108,163,176,225],"between":[109],"model":[112,168],"LLMs,":[115],"divide":[117],"completion":[121,156],"process":[122],"into":[123],"two":[124],"stages.":[125],"In":[126,155],"concept":[128],"enhancement":[129],"stage,":[130,158],"supplement":[132],"data":[135,221],"interacting":[137],"with":[138],"prompts":[140],"enrich":[145],"learned":[150],"model.":[154],"inference":[157],"adopted":[160],"iterative":[162,224],"strategy,":[164],"taking":[165,174],"output":[169],"as":[170,182],"content":[177],"previous":[180],"stage":[181],"context":[184],"enhance":[186],"inference,":[188],"which":[189],"improved":[190],"LLMs'":[192],"understanding":[193],"task.":[197],"Our":[198],"experiments":[199,213],"demonstrate":[200],"that":[201],"ColKGC":[202],"achieves":[203],"superior":[204],"results":[205],"across":[206],"various":[207],"standard":[208],"benchmarks.":[211],"Extensive":[212],"also":[214],"bear":[215],"out":[216],"ColKGC's":[217],"efectiveness":[218],"generated":[220],"framework":[226],"assisting":[228],"reasoning.":[230]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}