{"id":"https://openalex.org/W4391054902","doi":"https://doi.org/10.14778/3632093.3632108","title":"NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams","display_name":"NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4391054902","doi":"https://doi.org/10.14778/3632093.3632108"},"language":"en","primary_location":{"id":"doi:10.14778/3632093.3632108","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3632093.3632108","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","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/A5004586419","display_name":"Chaoyi Chen","orcid":"https://orcid.org/0009-0009-2119-9809"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoyi Chen","raw_affiliation_strings":["Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072455799","display_name":"Dechao Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dechao Gao","raw_affiliation_strings":["Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100367496","display_name":"Yanfeng Zhang","orcid":"https://orcid.org/0000-0002-9871-0304"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanfeng Zhang","raw_affiliation_strings":["Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052641511","display_name":"Qiange Wang","orcid":"https://orcid.org/0000-0002-4847-6070"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiange Wang","raw_affiliation_strings":["Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113100564","display_name":"Zhenbo Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenbo Fu","raw_affiliation_strings":["Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002546886","display_name":"Xuecang Zhang","orcid":"https://orcid.org/0009-0003-8638-2985"},"institutions":[{"id":"https://openalex.org/I4210160618","display_name":"Huawei Technologies (United Kingdom)","ror":"https://ror.org/056gzgs71","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210160618"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xuecang Zhang","raw_affiliation_strings":["Huawei Technologies Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Ltd","institution_ids":["https://openalex.org/I4210160618"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102163939","display_name":"Junhua Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210160618","display_name":"Huawei Technologies (United Kingdom)","ror":"https://ror.org/056gzgs71","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210160618"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Junhua Zhu","raw_affiliation_strings":["Huawei Technologies Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Ltd","institution_ids":["https://openalex.org/I4210160618"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100749025","display_name":"Yu Gu","orcid":"https://orcid.org/0000-0003-3634-2275"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Gu","raw_affiliation_strings":["Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072406974","display_name":"Ge Yu","orcid":"https://orcid.org/0000-0002-3171-8889"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Yu","raw_affiliation_strings":["Northeastern University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3794,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.90645839,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"17","issue":"3","first_page":"455","last_page":"468"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9995999932289124,"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":0.9995999932289124,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9976000189781189,"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"}},{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":0.996399998664856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8667685985565186},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.6730514764785767},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.6373156309127808},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5438665747642517},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5008420944213867},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.4881337583065033},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4291602075099945},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42513832449913025},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37832409143447876},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3571111261844635},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3293679356575012},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.3239187002182007},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.16425979137420654},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.15686410665512085},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.11547988653182983}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8667685985565186},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.6730514764785767},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.6373156309127808},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5438665747642517},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5008420944213867},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.4881337583065033},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4291602075099945},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42513832449913025},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37832409143447876},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3571111261844635},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3293679356575012},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.3239187002182007},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.16425979137420654},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.15686410665512085},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.11547988653182983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3632093.3632108","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3632093.3632108","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1602136775","https://openalex.org/W2057087916","https://openalex.org/W2143554828","https://openalex.org/W2551706664","https://openalex.org/W2912918068","https://openalex.org/W2913954081","https://openalex.org/W2914721378","https://openalex.org/W2917977646","https://openalex.org/W2970929262","https://openalex.org/W2974168418","https://openalex.org/W2979615946","https://openalex.org/W3013115102","https://openalex.org/W3019863187","https://openalex.org/W3026076535","https://openalex.org/W3134757439","https://openalex.org/W3139991122","https://openalex.org/W3193327410","https://openalex.org/W3194434277","https://openalex.org/W3201053014","https://openalex.org/W4210257598","https://openalex.org/W4221162710","https://openalex.org/W4242771733","https://openalex.org/W4282037596","https://openalex.org/W4283314525","https://openalex.org/W4283366315","https://openalex.org/W4288070868","https://openalex.org/W4292718518","https://openalex.org/W4301113013","https://openalex.org/W4320157521","https://openalex.org/W4366492495","https://openalex.org/W4367046738","https://openalex.org/W4379932299"],"related_works":["https://openalex.org/W4360995307","https://openalex.org/W2167004500","https://openalex.org/W2059461309","https://openalex.org/W1572762191","https://openalex.org/W2375516608","https://openalex.org/W2106570241","https://openalex.org/W3207785250","https://openalex.org/W4382459699","https://openalex.org/W6445124","https://openalex.org/W1994168535"],"abstract_inverted_index":{"Existing":[0],"Graph":[1],"Neural":[2],"Network":[3],"(GNN)":[4],"training":[5,52,85,91,106,131],"frameworks":[6,22],"have":[7,44],"been":[8],"designed":[9],"to":[10,46,94,108,117,157,172,179,205,216,227],"help":[11],"developers":[12],"easily":[13],"create":[14],"performant":[15],"GNN":[16,21,42,84,133,219],"implementations.":[17],"However,":[18],"most":[19,33],"existing":[20],"assume":[23],"that":[24,32,65,191,202],"the":[25,51,69,88,101,137,150,160,174],"input":[26,138],"graphs":[27,35],"are":[28,36],"static,":[29],"but":[30],"ignore":[31],"real-world":[34],"constantly":[37],"evolving.":[38],"Though":[39],"many":[40],"dynamic":[41,56,83,120,132,139,193,208,218],"models":[43],"emerged":[45],"learn":[47],"from":[48,61,225],"evolving":[49],"graphs,":[50],"process":[53],"of":[54,74,146,163,199,234],"these":[55],"GNNs":[57,63],"is":[58],"dramatically":[59],"different":[60],"traditional":[62,89],"in":[64],"it":[66,111],"captures":[67],"both":[68],"spatial":[70],"and":[71,148,195,229],"temporal":[72],"dependencies":[73,162],"graph":[75,140,188],"updates.":[76],"This":[77],"poses":[78],"new":[79],"challenges":[80],"for":[81,115,130],"designing":[82],"frameworks.":[86],"First,":[87],"batched":[90],"method":[92],"fails":[93],"capture":[95,159],"real-time":[96],"structural":[97],"evolution":[98],"information.":[99],"Second,":[100],"time-dependent":[102],"nature":[103],"makes":[104],"parallel":[105,169],"hard":[107],"design.":[109],"Third,":[110],"lacks":[112],"system":[113],"supports":[114,192],"users":[116,204],"efficiently":[118],"implement":[119],"GNNs.":[121,209],"In":[122],"this":[123],"paper,":[124],"we":[125],"present":[126],"NeutronStream,":[127],"a":[128,142,168,186,197],"framework":[129],"models.":[134],"NeutronStream":[135,166,183,221],"abstracts":[136],"into":[141],"chronologically":[143],"updated":[144],"stream":[145,151],"events":[147],"processes":[149],"with":[152],"an":[153,230],"optimized":[154],"sliding":[155],"window":[156],"incrementally":[158],"spatial-temporal":[161],"events.":[164],"Furthermore,":[165],"provides":[167,196],"execution":[170],"engine":[171],"tackle":[173],"sequential":[175],"event":[176],"processing":[177],"challenge":[178],"achieve":[180],"high":[181],"performance.":[182],"also":[184],"integrates":[185],"built-in":[187],"storage":[189],"structure":[190],"updates":[194],"set":[198],"easy-to-use":[200],"APIs":[201],"allow":[203],"express":[206],"their":[207],"Our":[210],"experimental":[211],"results":[212],"demonstrate":[213],"that,":[214],"compared":[215],"state-of-the-art":[217],"implementations,":[220],"achieves":[222],"speedups":[223],"ranging":[224],"1.48X":[226],"5.87X":[228],"average":[231],"accuracy":[232],"improvement":[233],"3.97%.":[235]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}