{"id":"https://openalex.org/W4416010531","doi":"https://doi.org/10.1109/jiot.2025.3630489","title":"A Hybrid Framework of Symbolic and Embedding-Based Logic for Temporal Knowledge Graph Reasoning","display_name":"A Hybrid Framework of Symbolic and Embedding-Based Logic for Temporal Knowledge Graph Reasoning","publication_year":2025,"publication_date":"2025-11-07","ids":{"openalex":"https://openalex.org/W4416010531","doi":"https://doi.org/10.1109/jiot.2025.3630489"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2025.3630489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3630489","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Internet of Things Journal","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/A5102702847","display_name":"Fengsong Sun","orcid":"https://orcid.org/0009-0001-3059-3308"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengsong Sun","raw_affiliation_strings":["Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-3059-3308","affiliations":[{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102744584","display_name":"Xianchao Zhang","orcid":"https://orcid.org/0000-0001-8925-8371"},"institutions":[{"id":"https://openalex.org/I4210092870","display_name":"Jiaxing University","ror":"https://ror.org/00j2a7k55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092870"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianchao Zhang","raw_affiliation_strings":["Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems, Jiaxing University, Jiaxing, China"],"raw_orcid":"https://orcid.org/0000-0001-8925-8371","affiliations":[{"raw_affiliation_string":"Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems, Jiaxing University, Jiaxing, China","institution_ids":["https://openalex.org/I4210092870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039663772","display_name":"Zhiqing Wei","orcid":"https://orcid.org/0000-0001-7940-2739"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqing Wei","raw_affiliation_strings":["Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7940-2739","affiliations":[{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101504448","display_name":"Jinyu Wang","orcid":"https://orcid.org/0009-0003-4843-8597"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyu Wang","raw_affiliation_strings":["Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-4843-8597","affiliations":[{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001714538","display_name":"Zhiyong Feng","orcid":"https://orcid.org/0000-0001-5322-222X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Feng","raw_affiliation_strings":["Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5322-222X","affiliations":[{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Ministry of Education, Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102024260","display_name":"Jun Lu","orcid":"https://orcid.org/0009-0003-0652-6812"},"institutions":[{"id":"https://openalex.org/I4210092870","display_name":"Jiaxing University","ror":"https://ror.org/00j2a7k55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092870"]},{"id":"https://openalex.org/I4210130112","display_name":"China Academy of Information and Communications Technology","ror":"https://ror.org/038dte259","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210130112","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Lu","raw_affiliation_strings":["Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems, Jiaxing University, Jiaxing, China","China Academy of Electronics and Information Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0003-0652-6812","affiliations":[{"raw_affiliation_string":"Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems, Jiaxing University, Jiaxing, China","institution_ids":["https://openalex.org/I4210092870"]},{"raw_affiliation_string":"China Academy of Electronics and Information Technology, Beijing, China","institution_ids":["https://openalex.org/I4210130112"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16507805,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"2","first_page":"2085","last_page":"2098"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.4180000126361847,"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":0.4180000126361847,"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.14650000631809235,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.07010000199079514,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/exploit","display_name":"Exploit","score":0.7013999819755554},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6366999745368958},{"id":"https://openalex.org/keywords/temporal-logic","display_name":"Temporal logic","score":0.5972999930381775},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.579800009727478},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5095999836921692},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4871000051498413},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45570001006126404},{"id":"https://openalex.org/keywords/interval-temporal-logic","display_name":"Interval temporal logic","score":0.43860000371932983}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8300999999046326},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7013999819755554},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6366999745368958},{"id":"https://openalex.org/C25016198","wikidata":"https://www.wikidata.org/wiki/Q781833","display_name":"Temporal logic","level":2,"score":0.5972999930381775},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5963000059127808},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.579800009727478},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5095999836921692},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4871000051498413},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48429998755455017},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45570001006126404},{"id":"https://openalex.org/C162670838","wikidata":"https://www.wikidata.org/wiki/Q6057295","display_name":"Interval temporal logic","level":3,"score":0.43860000371932983},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43070000410079956},{"id":"https://openalex.org/C4777664","wikidata":"https://www.wikidata.org/wiki/Q1536492","display_name":"Linear temporal logic","level":2,"score":0.41130000352859497},{"id":"https://openalex.org/C2779382394","wikidata":"https://www.wikidata.org/wiki/Q1464197","display_name":"Inductive logic programming","level":2,"score":0.3709999918937683},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32820001244544983},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3172000050544739},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C198008173","wikidata":"https://www.wikidata.org/wiki/Q1040040","display_name":"Computation tree logic","level":3,"score":0.28360000252723694},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.27639999985694885},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2669000029563904},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C3746660","wikidata":"https://www.wikidata.org/wiki/Q1068763","display_name":"Rule of inference","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25600001215934753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2025.3630489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2025.3630489","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1802935493","display_name":null,"funder_award_id":"2023YFC3305900","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"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":27,"referenced_works":["https://openalex.org/W1516111018","https://openalex.org/W1977970897","https://openalex.org/W2889782235","https://openalex.org/W2890410208","https://openalex.org/W2998313947","https://openalex.org/W2998528434","https://openalex.org/W3099845049","https://openalex.org/W3100187427","https://openalex.org/W3101611558","https://openalex.org/W3106844781","https://openalex.org/W3115318530","https://openalex.org/W3117206239","https://openalex.org/W3182741322","https://openalex.org/W3187578449","https://openalex.org/W3196669501","https://openalex.org/W3211621103","https://openalex.org/W4226108537","https://openalex.org/W4226350104","https://openalex.org/W4285140697","https://openalex.org/W4285600519","https://openalex.org/W4367047514","https://openalex.org/W4385285758","https://openalex.org/W4385430245","https://openalex.org/W4385574100","https://openalex.org/W4389518808","https://openalex.org/W4393156643","https://openalex.org/W4396802144"],"related_works":[],"abstract_inverted_index":{"Temporal":[0,83],"knowledge":[1,173],"graph":[2],"(TKG)":[3],"reasoning":[4,18],"involves":[5],"inferring":[6],"future":[7,145],"unknown":[8],"facts":[9,42],"based":[10],"on":[11,150],"historical":[12],"data.":[13],"Current":[14],"approaches":[15],"to":[16,64,143],"temporal":[17,41,48,73,102,113,119,129,140],"can":[19],"be":[20],"broadly":[21],"categorized":[22],"into":[23],"two":[24,107],"main":[25],"paradigms:":[26],"embedding-based":[27,33],"methods":[28,34,46,61],"and":[29,71,121,139],"symbolic":[30,45,95],"methods.":[31],"While":[32],"excel":[35],"at":[36],"capturing":[37],"time":[38,70,138,163],"by":[39],"representing":[40],"as":[43,53],"vector,":[44],"exploit":[47,66],"dependencies":[49],"using":[50],"techniques":[51],"such":[52,191],"random":[54],"walks":[55],"for":[56,100],"inference":[57],"purposes.":[58],"However,":[59],"existing":[60],"often":[62],"fail":[63],"fully":[65,161],"both":[67],"the":[68],"inherent":[69],"intricate":[72],"relationship":[74,141],"patterns":[75,142],"simultaneously.":[76],"To":[77],"address":[78],"this":[79],"limitation,":[80],"we":[81],"propose":[82],"neural":[84,98],"probabilistic":[85],"logic":[86,96,114],"learning":[87],"(TNPLL),":[88],"an":[89],"innovative":[90],"framework":[91,167],"that":[92,155,185],"seamlessly":[93],"integrates":[94],"with":[97,117],"embeddings":[99],"robust":[101],"reasoning.":[103],"Our":[104],"approach":[105],"incorporates":[106],"key":[108],"components,":[109],"a":[110,122,127],"set":[111],"of":[112],"rules":[115],"equipped":[116],"explicit":[118],"relationships":[120],"scoring":[123],"module":[124],"implemented":[125],"through":[126],"novel":[128],"memory":[130],"network":[131],"architecture.":[132],"The":[133,181],"proposed":[134],"method":[135],"effectively":[136],"combines":[137],"predict":[144],"facts.":[146],"We":[147],"conducted":[148],"experiments":[149],"several":[151],"benchmark":[152],"datasets,":[153],"demonstrating":[154],"TNPLL":[156,186],"achieves":[157],"improved":[158],"performance":[159],"while":[160],"leveraging":[162],"information.":[164],"Specifically,":[165],"our":[166],"excels":[168],"in":[169,190],"scenarios":[170],"where":[171],"prior":[172],"is":[174],"available,":[175],"but":[176],"data":[177],"samples":[178],"are":[179],"sparse.":[180],"experimental":[182],"outcomes":[183],"show":[184],"outperforms":[187],"state-of-the-art":[188],"models":[189],"cases.":[192]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-07T00:00:00"}
