{"id":"https://openalex.org/W4406242654","doi":"https://doi.org/10.3724/2096-7004.di.2024.0038","title":"Automatic Construction of Knowledge Graphs from Scientific Literature for Copper-based Composites","display_name":"Automatic Construction of Knowledge Graphs from Scientific Literature for Copper-based Composites","publication_year":2024,"publication_date":"2024-12-01","ids":{"openalex":"https://openalex.org/W4406242654","doi":"https://doi.org/10.3724/2096-7004.di.2024.0038"},"language":"en","primary_location":{"id":"doi:10.3724/2096-7004.di.2024.0038","is_oa":true,"landing_page_url":"https://doi.org/10.3724/2096-7004.di.2024.0038","pdf_url":"https://www.sciengine.com/doi/pdf/77CB430CB8824493B8D7B349AF1FBFE4","source":{"id":"https://openalex.org/S4210186383","display_name":"Data Intelligence","issn_l":"2096-7004","issn":["2096-7004","2641-435X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.sciengine.com/doi/pdf/77CB430CB8824493B8D7B349AF1FBFE4","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102969941","display_name":"Zixuan Hu","orcid":"https://orcid.org/0000-0001-8142-8540"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zixuan Hu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101734204","display_name":"Jinguo You","orcid":"https://orcid.org/0000-0002-9118-3775"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinguo You","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Xingrui Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xingrui Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102657823","display_name":"Huaze Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huaze Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045221095","display_name":"Jingmei Tao","orcid":"https://orcid.org/0000-0002-8533-3327"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jingmei Tao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102780947","display_name":"Jianhong Yi","orcid":"https://orcid.org/0000-0003-2722-5464"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianhong Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3205,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66084211,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"6","issue":"4","first_page":"1168","last_page":"1189"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.8949000239372253,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.8949000239372253,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10215","display_name":"Semantic Web and Ontologies","score":0.8919000029563904,"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/copper","display_name":"Copper","score":0.6013628840446472},{"id":"https://openalex.org/keywords/composite-material","display_name":"Composite material","score":0.4504564106464386},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.39174243807792664},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.3014197051525116},{"id":"https://openalex.org/keywords/metallurgy","display_name":"Metallurgy","score":0.07558563351631165}],"concepts":[{"id":"https://openalex.org/C544778455","wikidata":"https://www.wikidata.org/wiki/Q753","display_name":"Copper","level":2,"score":0.6013628840446472},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.4504564106464386},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39174243807792664},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.3014197051525116},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.07558563351631165}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3724/2096-7004.di.2024.0038","is_oa":true,"landing_page_url":"https://doi.org/10.3724/2096-7004.di.2024.0038","pdf_url":"https://www.sciengine.com/doi/pdf/77CB430CB8824493B8D7B349AF1FBFE4","source":{"id":"https://openalex.org/S4210186383","display_name":"Data Intelligence","issn_l":"2096-7004","issn":["2096-7004","2641-435X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3724/2096-7004.di.2024.0038","is_oa":true,"landing_page_url":"https://doi.org/10.3724/2096-7004.di.2024.0038","pdf_url":"https://www.sciengine.com/doi/pdf/77CB430CB8824493B8D7B349AF1FBFE4","source":{"id":"https://openalex.org/S4210186383","display_name":"Data Intelligence","issn_l":"2096-7004","issn":["2096-7004","2641-435X"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7765730107","display_name":"\u5927\u6570\u636e\u8054\u673a\u5206\u6790\u5904\u7406\u667a\u80fd\u5316\u6280\u672f\u7814\u7a76","funder_award_id":"62062046","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"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406242654.pdf","grobid_xml":"https://content.openalex.org/works/W4406242654.grobid-xml"},"referenced_works_count":10,"referenced_works":["https://openalex.org/W2766362701","https://openalex.org/W2980932864","https://openalex.org/W3003265726","https://openalex.org/W3023094935","https://openalex.org/W3119497443","https://openalex.org/W3204412080","https://openalex.org/W4221131784","https://openalex.org/W4289334098","https://openalex.org/W6811906953","https://openalex.org/W6851379941"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4404995717","https://openalex.org/W2016187641","https://openalex.org/W4404725684","https://openalex.org/W4246450666","https://openalex.org/W4388998267","https://openalex.org/W4404385369","https://openalex.org/W2898370298"],"abstract_inverted_index":{"Providing":[0],"knowledge":[1,73,82],"graphs":[2,83],"for":[3,66],"materials":[4,14,36,81,132],"science":[5],"facilitates":[6],"understanding":[7],"of":[8,43,99,105,114],"the":[9,41,72,76,80,89,110,128],"key":[10],"data":[11,44],"such":[12],"as":[13],"structure,":[15],"property,":[16],"etc.":[17],"and":[18,45,57,86,102,120,135],"their":[19,118,137],"relations.":[20],"However,":[21],"very":[22],"little":[23],"work":[24],"has":[25],"been":[26],"devoted":[27],"to":[28,35],"it.":[29],"Meanwhile,":[30],"immediately":[31],"applying":[32],"machine":[33],"learning":[34],"computation":[37],"still":[38],"suffers":[39],"from":[40],"lack":[42],"costly":[46],"acquiring.":[47],"To":[48],"tackle":[49],"these":[50],"problems,":[51],"we":[52,70,126],"propose":[53],"literature-aid":[54],"automatic":[55],"entity":[56],"relation":[58],"extraction":[59],"by":[60,74,130],"deliberatively":[61],"designed":[62],"matching":[63],"rules,":[64],"especially":[65],"copper-based":[67,115],"composites.":[68],"Next,":[69],"fuse":[71],"calculating":[75],"semantics":[77],"similarity.":[78],"Finally,":[79],"are":[84,107],"constructed":[85],"visualized":[87],"on":[88,109],"Neo4j":[90],"graph":[91],"database.":[92],"The":[93],"experimental":[94],"results":[95],"show":[96],"a":[97],"total":[98],"6,154":[100],"entities":[101],"15,561":[103],"pairs":[104],"relations":[106],"extracted":[108],"69,600":[111],"open-accessed":[112],"documents":[113],"composites,":[116],"with":[117],"precision":[119],"accuracy":[121],"rates":[122],"over":[123],"80%.":[124],"Further,":[125],"exemplify":[127],"effectiveness":[129],"building":[131],"structure-property-value":[133],"meta-paths":[134],"analyzing":[136],"impacts.":[138]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}