{"id":"https://openalex.org/W2112965067","doi":"https://doi.org/10.1109/icde.2006.57","title":"Efficient Discovery of Emerging Frequent Patterns in ArbitraryWindows on Data Streams","display_name":"Efficient Discovery of Emerging Frequent Patterns in ArbitraryWindows on Data Streams","publication_year":2006,"publication_date":"2006-01-01","ids":{"openalex":"https://openalex.org/W2112965067","doi":"https://doi.org/10.1109/icde.2006.57","mag":"2112965067"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2006.57","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2006.57","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"22nd International Conference on Data Engineering (ICDE'06)","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/A5022525223","display_name":"Xiaoming Jin","orcid":"https://orcid.org/0000-0003-1531-3803"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoming Jin","raw_affiliation_strings":["Tsinghua University, China","Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042752090","display_name":"Xinqiang Zuo","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinqiang Zuo","raw_affiliation_strings":["Tsinghua University, China","Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101720092","display_name":"Kwok\u2010Yan Lam","orcid":"https://orcid.org/0000-0001-7479-7970"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kwok-Yan Lam","raw_affiliation_strings":["Tsinghua University, China","Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100373517","display_name":"Jianmin Wang","orcid":"https://orcid.org/0000-0001-6841-7943"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianmin Wang","raw_affiliation_strings":["Tsinghua University, China","Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100429010","display_name":"Jiaguang Sun","orcid":"https://orcid.org/0000-0002-5884-7939"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaguang Sun","raw_affiliation_strings":["Tsinghua University, China","Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5022525223"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12021686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"113","last_page":"113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9835000038146973,"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":0.9835000038146973,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9768999814987183,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8310939073562622},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.746513843536377},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7426352500915527},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6997714042663574},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.6988308429718018},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.6130021810531616},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.5529636144638062},{"id":"https://openalex.org/keywords/streaming-data","display_name":"Streaming data","score":0.515673041343689},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.48674464225769043},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.47372522950172424}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8310939073562622},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.746513843536377},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7426352500915527},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6997714042663574},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.6988308429718018},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.6130021810531616},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.5529636144638062},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.515673041343689},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.48674464225769043},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.47372522950172424},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icde.2006.57","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2006.57","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"22nd International Conference on Data Engineering (ICDE'06)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1484413656","https://openalex.org/W2119939946","https://openalex.org/W2141514928","https://openalex.org/W2533248932","https://openalex.org/W6628750762"],"related_works":["https://openalex.org/W127192698","https://openalex.org/W4389449520","https://openalex.org/W2360131081","https://openalex.org/W1572762191","https://openalex.org/W3207785250","https://openalex.org/W2985941356","https://openalex.org/W2991818765","https://openalex.org/W2106570241","https://openalex.org/W4360995307","https://openalex.org/W2167004500"],"abstract_inverted_index":{"This":[0,114],"paper":[1,115],"proposes":[2],"an":[3],"effective":[4],"data":[5,36,157,160],"mining":[6,134],"technique":[7],"for":[8,25],"finding":[9,177],"useful":[10,74,88,178],"patterns":[11,26,54,75,89,148],"in":[12,27,47,49,108,149,171,176],"streaming":[13,151],"sequences.":[14],"At":[15],"present,":[16],"typical":[17,50],"approaches":[18,44],"to":[19,23,64,82,95,126,142],"this":[20,96],"problem":[21,97],"are":[22,45,55,98],"search":[24,129],"a":[28,66,68,104,109,117,123,133,138,150],"fixed-size":[29],"window":[30,70,92],"sliding":[31],"through":[32],"the":[33,53,128,163],"stream":[34],"of":[35,42,146],"being":[37],"collected.":[38],"The":[39],"practical":[40],"values":[41],"such":[43],"limited":[46],"that,":[48],"application":[51],"scenarios,":[52],"emerging":[56,147],"and":[57,131,158,174],"it":[58,102],"is":[59,79],"difficult,":[60],"if":[61],"not":[62],"impossible,":[63],"determine":[65],"priori":[67],"suitable":[69],"size":[71],"within":[72],"which":[73,120],"may":[76],"exist.":[77],"It":[78],"therefore":[80],"desirable":[81],"devise":[83],"techniques":[84],"that":[85,136,162],"can":[86],"identify":[87],"with":[90],"arbitrary":[91],"sizes.":[93],"Attempts":[94],"challenging,":[99],"however,":[100],"because":[101],"requires":[103],"highly":[105],"efficient":[106,144],"searching":[107],"substantially":[110],"bigger":[111],"solution":[112],"space.":[113],"presents":[116],"new":[118],"method":[119,165],"includes":[121],"firstly":[122],"pruning":[124],"strategy":[125,135],"reduce":[127],"space":[130],"secondly":[132],"adopts":[137],"dynamic":[139],"index":[140],"structure":[141],"allow":[143],"discovery":[145],"sequence.":[152],"Experimental":[153],"results":[154],"on":[155],"real":[156],"synthetic":[159],"show":[161],"proposed":[164],"outperforms":[166],"other":[167],"existing":[168],"schemes":[169],"both":[170],"computational":[172],"efficiency":[173],"effectiveness":[175],"patterns.":[179]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}