{"id":"https://openalex.org/W2763519809","doi":"https://doi.org/10.1145/3186728.3164136","title":"Clustering stream data by exploring the evolution of density mountain","display_name":"Clustering stream data by exploring the evolution of density mountain","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2763519809","doi":"https://doi.org/10.1145/3186728.3164136","mag":"2763519809"},"language":"en","primary_location":{"id":"doi:10.1145/3186728.3164136","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3186728.3164136","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/A5079250744","display_name":"Shufeng Gong","orcid":"https://orcid.org/0000-0001-5898-5621"},"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":true,"raw_author_name":"Shufeng Gong","raw_affiliation_strings":["Northeastern University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Shenyang, 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, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Shenyang, 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/I118803816","display_name":"Liaoning University","ror":"https://ror.org/03xpwj629","country_code":"CN","type":"education","lineage":["https://openalex.org/I118803816"]},{"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 and Liaoning University, Shenyang, China"],"affiliations":[{"raw_affiliation_string":"Northeastern University and Liaoning University, Shenyang, China","institution_ids":["https://openalex.org/I9224756","https://openalex.org/I118803816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5079250744"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":3.1182,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.93473983,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"11","issue":"4","first_page":"393","last_page":"405"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","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/T12761","display_name":"Data Stream Mining Techniques","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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9977999925613403,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.8776650428771973},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.7670388221740723},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7157903909683228},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5870622992515564},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.5117961764335632},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4931947588920593},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.4852881133556366},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.4727034568786621},{"id":"https://openalex.org/keywords/determining-the-number-of-clusters-in-a-data-set","display_name":"Determining the number of clusters in a data set","score":0.4724096357822418},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.46895259618759155},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21802598237991333}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8776650428771973},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.7670388221740723},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7157903909683228},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5870622992515564},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.5117961764335632},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4931947588920593},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.4852881133556366},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.4727034568786621},{"id":"https://openalex.org/C149872217","wikidata":"https://www.wikidata.org/wiki/Q5265701","display_name":"Determining the number of clusters in a data set","level":5,"score":0.4724096357822418},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.46895259618759155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21802598237991333},{"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:10.1145/3186728.3164136","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3186728.3164136","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":28,"referenced_works":["https://openalex.org/W142212369","https://openalex.org/W155321260","https://openalex.org/W182707955","https://openalex.org/W1488788114","https://openalex.org/W1552074189","https://openalex.org/W1975852288","https://openalex.org/W1980435364","https://openalex.org/W2004254978","https://openalex.org/W2004625705","https://openalex.org/W2011396747","https://openalex.org/W2026297770","https://openalex.org/W2063598276","https://openalex.org/W2088340225","https://openalex.org/W2092335550","https://openalex.org/W2092799168","https://openalex.org/W2095897464","https://openalex.org/W2112482089","https://openalex.org/W2165835468","https://openalex.org/W2170936641","https://openalex.org/W2259448304","https://openalex.org/W2295100167","https://openalex.org/W2343620495","https://openalex.org/W2395123632","https://openalex.org/W2520037496","https://openalex.org/W2613529642","https://openalex.org/W3007826101","https://openalex.org/W4213009331","https://openalex.org/W4247624306"],"related_works":["https://openalex.org/W2559422900","https://openalex.org/W2892323093","https://openalex.org/W2394193399","https://openalex.org/W2738096727","https://openalex.org/W3174322327","https://openalex.org/W4240938748","https://openalex.org/W2036298232","https://openalex.org/W2782648987","https://openalex.org/W2363054820","https://openalex.org/W2074010472"],"abstract_inverted_index":{"Stream":[0],"clustering":[1,38,64,87,151,168],"is":[2,100,145,178],"a":[3,85,183],"fundamental":[4],"problem":[5],"in":[6,22,72,146],"many":[7],"streaming":[8],"data":[9,29,105,112,132],"analysis":[10],"applications.":[11],"Comparing":[12],"to":[13,34,53,102,137,164,180,182],"classical":[14],"batch-mode":[15],"clustering,":[16],"there":[17],"are":[18,30],"two":[19],"key":[20],"challenges":[21],"stream":[23,63,86,167],"clustering:":[24],"(i)":[25],"Given":[26,42],"that":[27,43,139],"input":[28],"changing":[31],"continuously,":[32],"how":[33,52],"incrementally":[35],"update":[36,68,141,185],"their":[37],"results":[39,155],"efficiently?":[40],"(ii)":[41],"clusters":[44,120],"continuously":[45],"evolve":[46],"with":[47],"the":[48,55,69,76,92,104,107,117,123,140,165,192,195,199,210],"evolution":[49,57,77,118,212],"of":[50,61,78,94,109,119,125,142,194],"data,":[51],"capture":[54],"cluster":[56,70,184,204,211],"activities?":[58],"Unfortunately,":[59],"most":[60],"existing":[62],"algorithms":[65],"can":[66],"neither":[67],"result":[71],"real-time":[73],"nor":[74],"track":[75,116],"clusters.":[79],"In":[80],"this":[81],"paper,":[82],"we":[83],"propose":[84],"algorithm":[88,177],"EDMStream":[89,207],"by":[90,121],"exploring":[91],"Evolution":[93],"Density":[95],"Mountain.":[96],"The":[97,153],"density":[98,126,143],"mountain":[99],"used":[101],"abstract":[103],"distribution,":[106],"changes":[108,124],"which":[110,148],"indicate":[111],"distribution":[113],"evolution.":[114],"We":[115,128],"monitoring":[122],"mountains.":[127],"further":[129],"provide":[130],"efficient":[131],"structures":[133],"and":[134,158,174,197],"filtering":[135],"schemes":[136],"ensure":[138],"mountains":[144],"real-time,":[147],"makes":[149],"online":[150],"possible.":[152],"experimental":[154],"on":[156],"synthetic":[157],"real":[159],"datasets":[160],"show":[161],"that,":[162],"comparing":[163],"state-of-the-art":[166],"algorithms,":[169],"e.g.,":[170],"D-Stream,":[171],"DenStream,":[172],"DBSTREAM":[173],"MR-Stream,":[175],"our":[176],"able":[179],"response":[181],"much":[186],"faster":[187,190],"(say":[188],"7-15x":[189],"than":[191],"best":[193],"competitors)":[196],"at":[198],"same":[200],"time":[201],"achieve":[202],"comparable":[203],"quality.":[205],"Furthermore,":[206],"successfully":[208],"captures":[209],"activities.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}