{"id":"https://openalex.org/W4403577866","doi":"https://doi.org/10.1145/3627673.3679876","title":"Attentional Neural Integral Equation for Temporal Knowledge Graph Forecasting","display_name":"Attentional Neural Integral Equation for Temporal Knowledge Graph Forecasting","publication_year":2024,"publication_date":"2024-10-20","ids":{"openalex":"https://openalex.org/W4403577866","doi":"https://doi.org/10.1145/3627673.3679876"},"language":"en","primary_location":{"id":"doi:10.1145/3627673.3679876","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679876","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3627673.3679876?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3627673.3679876?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101230915","display_name":"Likang Xiao","orcid":"https://orcid.org/0009-0001-1346-1282"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Likang Xiao","raw_affiliation_strings":["Beihang University, Haidian Qu, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Haidian Qu, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zijie Chen","orcid":"https://orcid.org/0009-0004-5695-6770"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Zijie Chen","raw_affiliation_strings":["University of Toronto, Toronto, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027015677","display_name":"Richong Zhang","orcid":"https://orcid.org/0000-0002-1207-0300"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Richong Zhang","raw_affiliation_strings":["Beihang University, Haidian Qu, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Haidian Qu, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006061735","display_name":"Junfan Chen","orcid":"https://orcid.org/0000-0001-6807-0089"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfan Chen","raw_affiliation_strings":["Beihang University, Haidian Qu, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Haidian Qu, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101230915"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1599567,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4128","last_page":"4132"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9975000023841858,"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/T10320","display_name":"Neural Networks and Applications","score":0.9975000023841858,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9973000288009644,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9925000071525574,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6443868279457092},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5099226236343384},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4730333983898163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45247119665145874},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.41292983293533325},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2301674485206604}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6443868279457092},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5099226236343384},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4730333983898163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45247119665145874},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.41292983293533325},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2301674485206604}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627673.3679876","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679876","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3627673.3679876?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3627673.3679876","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627673.3679876","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3627673.3679876?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1421742111","display_name":null,"funder_award_id":"U23B2056","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2082826544","display_name":null,"funder_award_id":"Postdoctoral","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2376276132","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5030940285","display_name":null,"funder_award_id":"2023M","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G5939423041","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8863666567","display_name":null,"funder_award_id":"and No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8951484681","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8955107213","display_name":null,"funder_award_id":"Major","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320311582","display_name":"Idaho State University","ror":"https://ror.org/0162z8b04"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403577866.pdf","grobid_xml":"https://content.openalex.org/works/W4403577866.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1969013469","https://openalex.org/W2022166150","https://openalex.org/W2728059831","https://openalex.org/W2747329762","https://openalex.org/W2798864014","https://openalex.org/W2889782235","https://openalex.org/W2914592219","https://openalex.org/W2998528434","https://openalex.org/W3097986917","https://openalex.org/W3103296573","https://openalex.org/W3173365702","https://openalex.org/W3182741322","https://openalex.org/W3196669501","https://openalex.org/W3211666987","https://openalex.org/W4247950230","https://openalex.org/W4300978720","https://openalex.org/W4367047514","https://openalex.org/W4382239895","https://openalex.org/W4385574100"],"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":{"Temporal":[0],"Knowledge":[1],"Graph":[2,130],"Forecasting":[3],"(TKGF)":[4],"aims":[5],"to":[6,27,39,54,74,85,96,136,153],"forecast":[7],"the":[8,19,30,40,48,82,86,97,101,115,128,138,155,180],"missing":[9],"entities":[10],"or":[11],"relations":[12],"at":[13,70],"a":[14,75],"specific":[15],"timestamp":[16,69],"when":[17],"only":[18,67],"historical":[20,31,64,120],"information":[21,32],"is":[22,25,151],"observed.":[23],"It":[24],"crucial":[26],"accurately":[28],"identify":[29],"of":[33,144,159],"complex":[34],"temporal":[35,142],"relational":[36],"graphs":[37],"related":[38],"query.":[41,98],"Existing":[42],"works,":[43],"e.g.,":[44],"TANGO,":[45],"have":[46],"exploited":[47,152],"Neural":[49,108],"Ordinary":[50],"Differential":[51],"Equation":[52,110,149],"(NODE)":[53],"TKGF.":[55],"However,":[56],"TANGO":[57,62,80],"encounters":[58],"two":[59],"limitations.":[60],"First,":[61],"observes":[63],"facts":[65,91],"with":[66,186],"one":[68],"each":[71],"step,":[72],"leading":[73],"long-term":[76],"forgetting":[77],"problem.":[78],"Second,":[79],"gives":[81],"same":[83],"weight":[84],"entire":[87],"history":[88],"graph,":[89],"including":[90],"that":[92],"are":[93],"not":[94],"relevant":[95],"To":[99,123],"tackle":[100],"above":[102],"limitations,":[103],"this":[104],"paper":[105],"utilizes":[106],"Attentional":[107],"Integral":[109,148],"for":[111],"TKGF":[112],"(tIE),":[113],"enabling":[114],"global":[116],"interaction":[117],"between":[118],"query-related":[119],"graph":[121,139],"sequences.":[122],"achieve":[124],"this,":[125],"we":[126],"employ":[127],"Relational":[129],"Convolutional":[131],"Network":[132],"and":[133,141,157,171],"Fourier-type":[134],"Transformer":[135],"model":[137],"structure":[140],"evolution":[143],"TKG.":[145],"The":[146,162],"Iterative":[147],"Solver":[150],"enhance":[154],"accuracy":[156],"robustness":[158],"numerical":[160],"solutions.":[161],"proposed":[163],"method":[164],"outperforms":[165],"baseline":[166],"models":[167],"regarding":[168],"several":[169],"metrics":[170],"inference":[172],"speed":[173],"on":[174,179],"four":[175],"benchmark":[176],"datasets,":[177],"especially":[178],"long":[181],"horizontal":[182],"link":[183],"forecasting":[184],"task":[185],"irregular":[187],"time":[188],"intervals.":[189]},"counts_by_year":[],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
