{"id":"https://openalex.org/W7124169520","doi":"https://doi.org/10.1109/icpads67057.2025.11323106","title":"CondAlign: Condition-Aware Cross Domain Account Alignment Based on Large Language Models","display_name":"CondAlign: Condition-Aware Cross Domain Account Alignment Based on Large Language Models","publication_year":2025,"publication_date":"2025-12-14","ids":{"openalex":"https://openalex.org/W7124169520","doi":"https://doi.org/10.1109/icpads67057.2025.11323106"},"language":null,"primary_location":{"id":"doi:10.1109/icpads67057.2025.11323106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11323106","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","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/A5121756966","display_name":"Hang Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hang Lin","raw_affiliation_strings":["School of Artificial Intelligence, Guangzhou University,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Guangzhou University,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123016182","display_name":"Zuolin Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuolin Feng","raw_affiliation_strings":["School of Artificial Intelligence, Guangzhou University,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Guangzhou University,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123041241","display_name":"Canyong Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Canyong Cai","raw_affiliation_strings":["School of Artificial Intelligence, Guangzhou University,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Guangzhou University,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122999875","display_name":"Ziyang Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyang Xie","raw_affiliation_strings":["School of Artificial Intelligence, Guangzhou University,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Guangzhou University,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009888316","display_name":"Y\u00fcn Peng","orcid":"https://orcid.org/0000-0001-6358-2333"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Peng","raw_affiliation_strings":["School of Artificial Intelligence, Guangzhou University,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Guangzhou University,Guangzhou,China","institution_ids":["https://openalex.org/I37987034"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78886716,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.7188000082969666,"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":0.7188000082969666,"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/T12127","display_name":"Software System Performance and Reliability","score":0.03669999912381172,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.03359999880194664,"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/set","display_name":"Set (abstract data type)","score":0.5231000185012817},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5175999999046326},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.49570000171661377},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4131999909877777},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.39590001106262207},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.35179999470710754},{"id":"https://openalex.org/keywords/conditional-probability","display_name":"Conditional probability","score":0.33379998803138733}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7960000038146973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5584999918937683},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5231000185012817},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5175999999046326},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.49570000171661377},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.42500001192092896},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4131999909877777},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.39590001106262207},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3849000036716461},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.35179999470710754},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3192000091075897},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpads67057.2025.11323106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpads67057.2025.11323106","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 31th International Conference on Parallel and Distributed Systems (ICPADS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5843960046768188,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G7250102513","display_name":null,"funder_award_id":"62472116","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8871828789","display_name":null,"funder_award_id":"2023YFC3321300","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2741750617","https://openalex.org/W2808284704","https://openalex.org/W2962916648","https://openalex.org/W2965373594","https://openalex.org/W2997062749","https://openalex.org/W3034906292","https://openalex.org/W3035191547","https://openalex.org/W3098038527","https://openalex.org/W3146701396","https://openalex.org/W4224308031","https://openalex.org/W4380433185","https://openalex.org/W4385569986","https://openalex.org/W4391621203","https://openalex.org/W4393305357","https://openalex.org/W4400910128","https://openalex.org/W4402672076","https://openalex.org/W4404781485","https://openalex.org/W4406611644","https://openalex.org/W4412887951","https://openalex.org/W4414394745"],"related_works":[],"abstract_inverted_index":{"Account":[0],"alignment":[1,22,55,106],"plays":[2],"a":[3,64,84,91,99],"significant":[4],"role":[5],"in":[6],"various":[7],"domains":[8],"such":[9],"as":[10],"identity":[11],"recognition,":[12],"security":[13],"monitoring,":[14],"and":[15],"public":[16],"opinion":[17],"analysis.":[18],"However,":[19],"existing":[20,35,128],"account":[21,41,54,121],"methods":[23,36],"largely":[24],"rely":[25],"on":[26,118],"knowledge":[27],"graphs,":[28],"which":[29],"is":[30,87,108],"very":[31],"costly.":[32],"More":[33],"importantly,":[34],"do":[37],"not":[38],"support":[39],"conditionconstrained":[40],"alignment,":[42],"thereby":[43],"limiting":[44],"practical":[45],"applicability.":[46],"In":[47],"this":[48],"paper,":[49],"we":[50],"propose":[51],"CondAlign,":[52],"an":[53],"method":[56,61],"under":[57],"conditional":[58,69,104],"constraints.":[59],"The":[60],"first":[62],"employs":[63],"large":[65,100],"language":[66,101],"model":[67,102],"(LLM)-based":[68,103],"semantic":[70,76,112],"extraction":[71],"technique":[72],"to":[73,89,110],"identify":[74],"key":[75],"features":[77],"that":[78,124],"meet":[79],"the":[80],"specified":[81],"constraints;":[82],"then,":[83],"filtering":[85],"mechanism":[86],"proposed":[88],"generate":[90],"set":[92],"of":[93],"highly":[94],"relevant":[95],"candidate":[96,114],"accounts;":[97],"finally,":[98],"constraint":[105],"determination":[107],"used":[109],"perform":[111],"verification":[113],"accounts.":[115],"Experimental":[116],"results":[117],"multiple":[119],"real-world":[120],"datasets":[122],"verify":[123],"CondAlign":[125],"significantly":[126],"outperforms":[127],"baseline":[129],"methods.":[130]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-01-15T00:00:00"}