{"id":"https://openalex.org/W2896592258","doi":"https://doi.org/10.1109/ijcnn.2018.8489644","title":"Temporal Link Prediction Using Cluster and Temporal Information Based Motif Feature","display_name":"Temporal Link Prediction Using Cluster and Temporal Information Based Motif Feature","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2896592258","doi":"https://doi.org/10.1109/ijcnn.2018.8489644","mag":"2896592258"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2018.8489644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","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/A5101528730","display_name":"Yi Li","orcid":"https://orcid.org/0000-0001-7252-0281"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Li","raw_affiliation_strings":["College of Computer and Control Engineering, Nankai University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103172652","display_name":"Yanlong Wen","orcid":"https://orcid.org/0000-0002-8006-9109"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanlong Wen","raw_affiliation_strings":["College of Computer and Control Engineering, Nankai University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101447006","display_name":"Peng Nie","orcid":"https://orcid.org/0000-0002-5526-3401"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Nie","raw_affiliation_strings":["College of Computer and Control Engineering, Nankai University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062064974","display_name":"Xiaojie Yuan","orcid":"https://orcid.org/0000-0002-5876-6856"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojie Yuan","raw_affiliation_strings":["College of Computer and Control Engineering, Nankai University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.13318844,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"390","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7498387694358826},{"id":"https://openalex.org/keywords/motif","display_name":"Motif (music)","score":0.631077766418457},{"id":"https://openalex.org/keywords/concatenation","display_name":"Concatenation (mathematics)","score":0.5916661024093628},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5377035737037659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.52169269323349},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4493902921676636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3603626489639282},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34132498502731323},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09946432709693909}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7498387694358826},{"id":"https://openalex.org/C32276052","wikidata":"https://www.wikidata.org/wiki/Q908349","display_name":"Motif (music)","level":2,"score":0.631077766418457},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.5916661024093628},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5377035737037659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.52169269323349},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4493902921676636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3603626489639282},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34132498502731323},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09946432709693909},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2018.8489644","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2018.8489644","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W202590266","https://openalex.org/W1556758605","https://openalex.org/W1976526581","https://openalex.org/W1979104937","https://openalex.org/W2003707464","https://openalex.org/W2009130514","https://openalex.org/W2019863805","https://openalex.org/W2021579368","https://openalex.org/W2022322548","https://openalex.org/W2026417691","https://openalex.org/W2030470432","https://openalex.org/W2036433616","https://openalex.org/W2037933327","https://openalex.org/W2117030594","https://openalex.org/W2131681506","https://openalex.org/W2148762636","https://openalex.org/W2153204928","https://openalex.org/W2153624566","https://openalex.org/W2154454189","https://openalex.org/W2157312249","https://openalex.org/W2157762631","https://openalex.org/W2172174689","https://openalex.org/W2188738450","https://openalex.org/W2199530723","https://openalex.org/W2587449827","https://openalex.org/W2741796212","https://openalex.org/W2768375068","https://openalex.org/W2964126306","https://openalex.org/W3099768174","https://openalex.org/W3101251439","https://openalex.org/W3103858635","https://openalex.org/W4232932184","https://openalex.org/W6785582754"],"related_works":["https://openalex.org/W2373577936","https://openalex.org/W4387678054","https://openalex.org/W3095575180","https://openalex.org/W2389596151","https://openalex.org/W4221148444","https://openalex.org/W4226054107","https://openalex.org/W4306784355","https://openalex.org/W4246226292","https://openalex.org/W2150768546","https://openalex.org/W3091984855"],"abstract_inverted_index":{"Predicting":[0],"future":[1],"link":[2,24,161],"states":[3],"of":[4,29,56,64,87,108,128,142,154,166],"a":[5,50,70,126,146,164],"temporal":[6,23,91,101,132,167],"network":[7,112],"from":[8,15,19,138],"past":[9],"evolution":[10],"is":[11,37,59,123],"an":[12],"important":[13],"task":[14,58],"application":[16],"perspective.":[17],"Different":[18],"static":[20],"networks":[21],"analysis,":[22],"prediction":[25,162],"considers":[26],"the":[27,30,47,65,90,106,129,139,152,155],"trends":[28],"links":[31],"as":[32,98,100],"time":[33],"goes":[34],"by,":[35],"which":[36,79,169],"proved":[38],"can":[39,80],"achieve":[40],"higher":[41],"performance":[42],"than":[43],"that":[44],"only":[45],"exploring":[46],"interactions":[48],"at":[49],"specific":[51],"moment.":[52],"The":[53],"key":[54],"challenge":[55],"this":[57],"to":[60,104,144],"obtain":[61],"effective":[62],"features":[63,136],"evolving":[66],"network.":[67,92],"We":[68,93,150],"propose":[69],"novel":[71],"supervised":[72],"method":[73],"CTMF":[74,156],"based":[75,134],"on":[76,114,125,163],"motif":[77,116,135],"feature,":[78],"characterize":[81],"nearly":[82],"complete":[83],"local":[84],"topological":[85],"characteristic":[86],"node-pairs":[88],"in":[89],"also":[94],"attach":[95],"cluster":[96,130],"information":[97,133],"well":[99],"transition":[102,113],"factor":[103],"capture":[105,145],"influence":[107],"global":[109],"structure":[110],"and":[111,131],"each":[115],"over":[117],"time.":[118],"An":[119],"unsupervised":[120],"learning":[121],"strategy":[122],"used":[124],"concatenation":[127],"(CTMF)":[137],"continuous":[140],"sets":[141],"snapshots":[143],"better":[147],"feature":[148],"representation.":[149],"validate":[151],"effectiveness":[153],"by":[157],"utilizing":[158],"it":[159],"for":[160],"number":[165],"datasets,":[168],"shows":[170],"our":[171],"approach":[172],"outperforms":[173],"state-of-art":[174],"methods":[175],"using":[176],"other":[177],"features.":[178]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}