{"id":"https://openalex.org/W4406461807","doi":"https://doi.org/10.1109/bigdata62323.2024.10825070","title":"Aligning Knowledge Graphs Provided by Humans and Generated by Neural Networks","display_name":"Aligning Knowledge Graphs Provided by Humans and Generated by Neural Networks","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406461807","doi":"https://doi.org/10.1109/bigdata62323.2024.10825070"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5111184837","display_name":"Tinghui Li","orcid":"https://orcid.org/0009-0009-3121-8997"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tangrui Li","raw_affiliation_strings":["Temple University,Computer &#x0026; Information Sciences,Philadelphia,USA"],"affiliations":[{"raw_affiliation_string":"Temple University,Computer &#x0026; Information Sciences,Philadelphia,USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101345688","display_name":"Jun Zhou","orcid":"https://orcid.org/0009-0004-7737-8949"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["Temple University,Computer &#x0026; Information Sciences,Philadelphia,USA"],"affiliations":[{"raw_affiliation_string":"Temple University,Computer &#x0026; Information Sciences,Philadelphia,USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102406829","display_name":"Hongzheng Wang","orcid":"https://orcid.org/0009-0001-5341-9548"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongzheng Wang","raw_affiliation_strings":["Temple University,Computer &#x0026; Information Sciences,Philadelphia,USA"],"affiliations":[{"raw_affiliation_string":"Temple University,Computer &#x0026; Information Sciences,Philadelphia,USA","institution_ids":["https://openalex.org/I84392919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5111184837"],"corresponding_institution_ids":["https://openalex.org/I84392919"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23846199,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3441","last_page":"3447"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9944999814033508,"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":0.9944999814033508,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9799000024795532,"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":0.9735000133514404,"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":0.705101490020752},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5847093462944031},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5101733207702637},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41663533449172974}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.705101490020752},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5847093462944031},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5101733207702637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41663533449172974}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W83940682","https://openalex.org/W1982786963","https://openalex.org/W2015844562","https://openalex.org/W2021990760","https://openalex.org/W2065204741","https://openalex.org/W2122538988","https://openalex.org/W2250635077","https://openalex.org/W2343867888","https://openalex.org/W2528474336","https://openalex.org/W2561529111","https://openalex.org/W2808284704","https://openalex.org/W2888313207","https://openalex.org/W2921000712","https://openalex.org/W2951936329","https://openalex.org/W2966581343","https://openalex.org/W2980850196","https://openalex.org/W2988571238","https://openalex.org/W3035628711","https://openalex.org/W3041064262","https://openalex.org/W3093531652","https://openalex.org/W3096932862","https://openalex.org/W3128376221","https://openalex.org/W3212053370","https://openalex.org/W4200450299","https://openalex.org/W4205199576","https://openalex.org/W4230097545","https://openalex.org/W4288083725","https://openalex.org/W4293507378","https://openalex.org/W4385764354","https://openalex.org/W4386071707","https://openalex.org/W4388144143","https://openalex.org/W6603420235","https://openalex.org/W6748744355","https://openalex.org/W6754655096","https://openalex.org/W6760444480"],"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":{"In":[0],"this":[1],"paper,":[2],"an":[3],"approach":[4,40],"that":[5,64,79,97,112],"extracts":[6],"knowledge":[7,47],"graphs":[8],"(KGs)":[9],"from":[10,103],"neural":[11],"networks":[12],"(NNs)":[13],"and":[14,43,71,74],"aligns":[15],"the":[16,50,65,80,89,98],"generated":[17,105],"KGs":[18,102],"with":[19,49,115],"human-provided":[20,90,116],"ones":[21],"is":[22,31],"proposed":[23],"for":[24],"network":[25],"optimization":[26],"or":[27],"transparency":[28],"enhancement,":[29],"which":[30,53],"achieved":[32],"by":[33,106],"leveraging":[34],"Vector":[35],"Symbolic":[36],"Architectures":[37],"(VSAs).":[38],"The":[39],"identifies":[41],"entities":[42],"relations":[44],"of":[45],"NN\u2019s":[46],"along":[48],"training":[51],"process,":[52],"makes":[54],"it":[55],"a":[56],"plug-and-play":[57],"solution.":[58],"Experiments":[59],"on":[60,69,76,94],"synthetic":[61],"data":[62],"showed":[63,96],"matching":[66],"method":[67,99],"works":[68],"middle":[70],"small-size":[72],"KGs,":[73],"tests":[75,93],"MNIST":[77],"demonstrated":[78],"aligned":[81,113],"NN-generated":[82],"KG":[83],"could":[84,100],"be":[85],"very":[86],"close":[87],"to":[88],"ones.":[91],"Further":[92],"Text2KGBench":[95],"produce":[101],"embedding":[104],"backbone":[107],"large":[108],"language":[109],"models":[110],"(LLM)":[111],"well":[114],"labels":[117],"as":[118],"well.":[119]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
