{"id":"https://openalex.org/W3198512483","doi":"https://doi.org/10.1109/tkde.2021.3108224","title":"Knowledge Graph Completion by Jointly Learning Structural Features and Soft Logical Rules","display_name":"Knowledge Graph Completion by Jointly Learning Structural Features and Soft Logical Rules","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3198512483","doi":"https://doi.org/10.1109/tkde.2021.3108224","mag":"3198512483"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3108224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3108224","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5100653952","display_name":"Weidong Li","orcid":"https://orcid.org/0000-0002-0703-7952"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weidong Li","raw_affiliation_strings":["School of Computer Science, Wuhan University, 12390 Wuhan, Hubei, China, (e-mail: weidonghappy@whu.edu.cn)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, 12390 Wuhan, Hubei, China, (e-mail: weidonghappy@whu.edu.cn)","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078083652","display_name":"Rong Peng","orcid":"https://orcid.org/0000-0003-2330-9409"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Peng","raw_affiliation_strings":["School of Computer Science, Wuhan University, 12390 Wuhan, Hubei, China, (e-mail: rongpeng@whu.edu.cn)","[School of Computer Science, Wuhan University, 12390 Wuhan, Hubei, China, (e-mail: rongpeng@whu.edu.cn)]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, 12390 Wuhan, Hubei, China, (e-mail: rongpeng@whu.edu.cn)","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"[School of Computer Science, Wuhan University, 12390 Wuhan, Hubei, China, (e-mail: rongpeng@whu.edu.cn)]","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100685911","display_name":"Zhi Li","orcid":"https://orcid.org/0000-0002-4869-6778"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Li","raw_affiliation_strings":["College of Computer Science and Information Technology, Guangxi Normal University, 12388 Guilin, Guangxi, China, (e-mail: zhili@gxnu.edu.cn)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Information Technology, Guangxi Normal University, 12388 Guilin, Guangxi, China, (e-mail: zhili@gxnu.edu.cn)","institution_ids":["https://openalex.org/I29739308"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7743,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.87425092,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"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":0.9958000183105469,"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/T11719","display_name":"Data Quality and Management","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7911499738693237},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.648125171661377},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6268851161003113},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6233213543891907},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5691573023796082},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4971647560596466},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49472853541374207},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.41548216342926025},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33671924471855164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7911499738693237},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.648125171661377},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6268851161003113},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6233213543891907},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5691573023796082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4971647560596466},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49472853541374207},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.41548216342926025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33671924471855164},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2021.3108224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3108224","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320324116","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W651477617","https://openalex.org/W1533230146","https://openalex.org/W1552847225","https://openalex.org/W2022166150","https://openalex.org/W2081580037","https://openalex.org/W2094728533","https://openalex.org/W2107306718","https://openalex.org/W2184957013","https://openalex.org/W2250635077","https://openalex.org/W2251079237","https://openalex.org/W2283196293","https://openalex.org/W2296268288","https://openalex.org/W2300469216","https://openalex.org/W2467775179","https://openalex.org/W2511805592","https://openalex.org/W2563063592","https://openalex.org/W2604165577","https://openalex.org/W2604314403","https://openalex.org/W2728059831","https://openalex.org/W2755637027","https://openalex.org/W2759136286","https://openalex.org/W2769099080","https://openalex.org/W2797383850","https://openalex.org/W2888572441","https://openalex.org/W2927610379","https://openalex.org/W2950393809","https://openalex.org/W2962834633","https://openalex.org/W2963359213","https://openalex.org/W2966298461","https://openalex.org/W2984661639","https://openalex.org/W3099154743","https://openalex.org/W3102903061","https://openalex.org/W6608344535","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6631964550","https://openalex.org/W6678830454","https://openalex.org/W6712028060","https://openalex.org/W6718112784","https://openalex.org/W6740570033","https://openalex.org/W6745537798","https://openalex.org/W6745779156","https://openalex.org/W6750378536","https://openalex.org/W6755587638","https://openalex.org/W6772406930"],"related_works":["https://openalex.org/W2604454537","https://openalex.org/W2883748392","https://openalex.org/W2808284704","https://openalex.org/W2897702399","https://openalex.org/W4206028705","https://openalex.org/W2757431232","https://openalex.org/W2954554213","https://openalex.org/W2251363251","https://openalex.org/W4206547516","https://openalex.org/W4293236197"],"abstract_inverted_index":{"With":[0,183],"the":[1,39,68,75,118,143,164,190],"rapid":[2],"development":[3],"and":[4,27,74,87,89,124,168],"widespread":[5],"application":[6],"of":[7,19,38,72,85,122,147,166],"Knowledge":[8],"graphs":[9],"(KGs)":[10],"in":[11,53,156],"many":[12],"artificial":[13],"intelligence":[14],"tasks,":[15,42],"a":[16,108],"large":[17],"number":[18],"efforts":[20],"have":[21],"been":[22],"made":[23],"to":[24,45,66,80,92,141,161,179],"refine":[25],"them":[26],"increase":[28],"their":[29],"quality.":[30],"Knowedge":[31],"graph":[32,131],"embedding":[33,84],"(KGE)":[34],"has":[35],"become":[36],"one":[37,99],"main":[40],"refinement":[41],"which":[43,114,134],"aims":[44],"predict":[46,180],"missing":[47],"facts":[48],"based":[49],"on":[50,185],"existing":[51],"ones":[52],"KGs.":[54],"However,":[55],"there":[56],"are":[57,135],"still":[58],"mainly":[59],"two":[60,95],"difficult":[61],"unresolved":[62],"challenges:":[63],"(i)":[64],"how":[65,91],"leverage":[67],"local":[69,119,144],"structural":[70,145],"features":[71,121],"entities":[73,123,167],"potential":[76],"soft":[77,152],"logical":[78,126,153],"rules":[79,154],"learn":[81,117],"more":[82,176],"expressive":[83],"entites":[86],"relations;":[88],"(ii)":[90],"combine":[93],"these":[94,104],"learning":[96],"processes":[97],"into":[98],"unified":[100],"model.":[101],"To":[102],"conquer":[103],"problems,":[105],"we":[106,129,150,173],"propose":[107],"novel":[109],"KGE":[110],"model":[111],"named":[112],"JSSKGE,":[113],"can":[115,174],"\\textbf{J}ointly":[116],"\\textbf{S}tructural":[120],"\\textbf{S}oft":[125],"rules.":[127],"Firstly,":[128],"employ":[130],"attention":[132],"networks":[133],"specially":[136],"designed":[137],"for":[138],"graph-structured":[139],"data":[140],"aggregate":[142],"information":[146],"nodes.":[148],"Then,":[149],"utilize":[151],"implicated":[155],"KGs":[157],"as":[158],"an":[159],"expert":[160],"further":[162],"rectify":[163],"embeddings":[165,178],"relations.":[169],"By":[170],"jointly":[171],"learning,":[172],"obtain":[175],"informative":[177],"new":[181],"facts.":[182],"experiments":[184],"four":[186],"commonly":[187],"used":[188],"datasets,":[189],"JSSKGE":[191],"obtains":[192],"better":[193],"performance":[194],"than":[195],"state-of-the-art":[196],"approaches.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
