{"id":"https://openalex.org/W3046547435","doi":"https://doi.org/10.14778/3401960.3401973","title":"Data stream event prediction based on timing knowledge and state transitions","display_name":"Data stream event prediction based on timing knowledge and state transitions","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3046547435","doi":"https://doi.org/10.14778/3401960.3401973","mag":"3046547435"},"language":"en","primary_location":{"id":"doi:10.14778/3401960.3401973","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3401960.3401973","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/A5100380302","display_name":"Yan Li","orcid":"https://orcid.org/0000-0002-1126-9772"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["University of Massachusetts"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048219544","display_name":"Tingjian Ge","orcid":"https://orcid.org/0000-0003-2225-8291"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tingjian Ge","raw_affiliation_strings":["University of Massachusetts"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101498825","display_name":"Cindy Chen","orcid":"https://orcid.org/0000-0002-5358-7349"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cindy Chen","raw_affiliation_strings":["University of Massachusetts"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.043,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.82201259,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"13","issue":"10","first_page":"1779","last_page":"1792"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9998000264167786,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9901000261306763,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9900000095367432,"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":0.7937160730361938},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6033912897109985},{"id":"https://openalex.org/keywords/tuple","display_name":"Tuple","score":0.5980391502380371},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5522140264511108},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5504915118217468},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5391066670417786},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.5047568082809448},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.48771604895591736},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45804423093795776},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.45556214451789856},{"id":"https://openalex.org/keywords/complex-event-processing","display_name":"Complex event processing","score":0.4350319504737854},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.42448562383651733},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4242335557937622},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35277360677719116},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10573732852935791}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7937160730361938},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6033912897109985},{"id":"https://openalex.org/C118930307","wikidata":"https://www.wikidata.org/wiki/Q600590","display_name":"Tuple","level":2,"score":0.5980391502380371},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5522140264511108},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5504915118217468},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5391066670417786},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.5047568082809448},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.48771604895591736},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45804423093795776},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.45556214451789856},{"id":"https://openalex.org/C123606473","wikidata":"https://www.wikidata.org/wiki/Q907918","display_name":"Complex event processing","level":3,"score":0.4350319504737854},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.42448562383651733},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4242335557937622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35277360677719116},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10573732852935791},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"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:10.14778/3401960.3401973","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3401960.3401973","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1529533208","https://openalex.org/W1560724230","https://openalex.org/W1607867898","https://openalex.org/W1736726159","https://openalex.org/W1973026225","https://openalex.org/W2005368955","https://openalex.org/W2009797711","https://openalex.org/W2011422027","https://openalex.org/W2020571458","https://openalex.org/W2029538739","https://openalex.org/W2045478235","https://openalex.org/W2061860832","https://openalex.org/W2087258353","https://openalex.org/W2110089022","https://openalex.org/W2119885577","https://openalex.org/W2127795553","https://openalex.org/W2133564696","https://openalex.org/W2137424052","https://openalex.org/W2145646637","https://openalex.org/W2153836901","https://openalex.org/W2161484642","https://openalex.org/W2182578591","https://openalex.org/W2296319761","https://openalex.org/W2557283755","https://openalex.org/W2576565884","https://openalex.org/W2579923771","https://openalex.org/W2755092149","https://openalex.org/W2759045585","https://openalex.org/W2774898839","https://openalex.org/W2798056406","https://openalex.org/W2884593183","https://openalex.org/W2950133940","https://openalex.org/W2952770886","https://openalex.org/W2954452271","https://openalex.org/W2962975498","https://openalex.org/W2964308564","https://openalex.org/W2987119394","https://openalex.org/W3022458846","https://openalex.org/W4233955759","https://openalex.org/W4238284510","https://openalex.org/W6745537798","https://openalex.org/W6745857082"],"related_works":["https://openalex.org/W2044761590","https://openalex.org/W2118924829","https://openalex.org/W4253061173","https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W1496794085","https://openalex.org/W2570600173","https://openalex.org/W2151831402","https://openalex.org/W2157032266","https://openalex.org/W2949310134"],"abstract_inverted_index":{"We":[0,80,112],"study":[1],"a":[2,14,29,75,82,186],"practical":[3],"problem":[4],"of":[5,44,62,74,85,153],"predicting":[6],"the":[7,60,67,72,93,98,110,157,161],"upcoming":[8],"events":[9],"in":[10,128,192],"data":[11,76,100],"streams":[12],"using":[13],"novel":[15],"approach.":[16],"Treating":[17],"event":[18,25,39,135,172],"time":[19],"orders":[20],"as":[21],"relationship":[22],"types":[23],"between":[24,139],"entities,":[26],"we":[27,54,65],"build":[28],"dynamic":[30],"knowledge":[31,46,57],"graph":[32,47,95,168],"and":[33,104,106,122,131,141,171],"use":[34],"it":[35],"to":[36,150,178],"predict":[37],"future":[38],"timing.":[40],"A":[41],"unique":[42],"aspect":[43],"this":[45],"embedding":[48,103],"approach":[49,115],"for":[50,87,91,102,107,134],"prediction":[51],"is":[52,174,189],"that":[53,124,160],"enhance":[55],"conventional":[56],"graphs":[58],"with":[59,116],"notion":[61],"\"states\"---in":[63],"what":[64],"call":[66],"ephemeral":[68],"state":[69,73],"nodes---to":[70],"characterize":[71],"stream":[77,96,120,162],"over":[78,175],"time.":[79],"devise":[81],"complete":[83],"set":[84],"methods":[86],"learning":[88],"relevant":[89],"events,":[90],"building":[92],"event-order":[94],"from":[97],"original":[99],"stream,":[101],"prediction,":[105,137],"theoretically":[108],"bounding":[109],"complexity.":[111],"evaluate":[113],"our":[114,125,151],"four":[117],"real":[118],"world":[119],"datasets":[121],"find":[123],"method":[126],"results":[127],"high":[129],"precision":[130],"recall":[132],"values":[133],"timing":[136],"ranging":[138],"0.7":[140],"nearly":[142],"1,":[143],"significantly":[144],"outperforming":[145],"baseline":[146],"approaches.":[147],"Moreover,":[148],"due":[149],"choice":[152],"efficient":[154],"translation-based":[155],"embedding,":[156],"overall":[158],"throughput":[159],"system":[163],"can":[164],"handle,":[165],"including":[166,196],"continuous":[167],"building,":[169],"training,":[170],"predictions,":[173],"one":[176],"thousand":[177,180],"sixty":[179],"tuples":[181],"per":[182],"second":[183],"even":[184],"on":[185],"personal":[187],"computer---which":[188],"especially":[190],"important":[191],"resource":[193],"constrained":[194],"environments,":[195],"edge":[197],"computing.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
