{"id":"https://openalex.org/W3168054278","doi":"https://doi.org/10.1109/cscwd49262.2021.9437641","title":"Multi-resolution Odd Sketch for Mining Jaccard Similarities between Dynamic Streaming Sets","display_name":"Multi-resolution Odd Sketch for Mining Jaccard Similarities between Dynamic Streaming Sets","publication_year":2021,"publication_date":"2021-05-05","ids":{"openalex":"https://openalex.org/W3168054278","doi":"https://doi.org/10.1109/cscwd49262.2021.9437641","mag":"3168054278"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd49262.2021.9437641","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd49262.2021.9437641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103068268","display_name":"Qingjun Xiao","orcid":"https://orcid.org/0000-0001-8348-6277"},"institutions":[{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingjun Xiao","raw_affiliation_strings":["Purple Mountain Laboratories, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purple Mountain Laboratories, Nanjing, China","institution_ids":["https://openalex.org/I4210155350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110533413","display_name":"Lin Wen","orcid":"https://orcid.org/0009-0009-4042-1006"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Wen","raw_affiliation_strings":["School of Cyber Science & Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science & Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101975762","display_name":"Quanwei Zhang","orcid":"https://orcid.org/0000-0001-7541-7917"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quanwei Zhang","raw_affiliation_strings":["School of Cyber Science & Engineering, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science & Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5113,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59607135,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"99","issue":null,"first_page":"198","last_page":"203"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9991999864578247,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9987000226974487,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9983999729156494,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/jaccard-index","display_name":"Jaccard index","score":0.8580117225646973},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8363682627677917},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.7177668809890747},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6788103580474854},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5797296762466431},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5758810639381409},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.4270504117012024},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3723523020744324},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3360760807991028},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2738257646560669},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26674601435661316},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.17313644289970398},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09798336029052734}],"concepts":[{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.8580117225646973},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8363682627677917},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.7177668809890747},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6788103580474854},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5797296762466431},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5758810639381409},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4270504117012024},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3723523020744324},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3360760807991028},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2738257646560669},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26674601435661316},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.17313644289970398},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09798336029052734},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd49262.2021.9437641","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd49262.2021.9437641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G447178272","display_name":"\u6d77\u91cf\u7f51\u7edc\u6d41\u91cf\u6570\u636e\u7684\u8de8\u65f6\u7a7a\u57df\u534f\u540c\u5206\u6790\u548c\u6027\u80fd\u4f18\u5316\u7814\u7a76","funder_award_id":"61872080","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1502916507","https://openalex.org/W1967373117","https://openalex.org/W1982092405","https://openalex.org/W2008365755","https://openalex.org/W2025051251","https://openalex.org/W2029852131","https://openalex.org/W2034302520","https://openalex.org/W2060170830","https://openalex.org/W2081193615","https://openalex.org/W2099480861","https://openalex.org/W2132069633","https://openalex.org/W2140431670","https://openalex.org/W2152565070","https://openalex.org/W2946064759","https://openalex.org/W2963924281","https://openalex.org/W3001692356","https://openalex.org/W6629956336"],"related_works":["https://openalex.org/W1994775821","https://openalex.org/W2012019886","https://openalex.org/W2091133150","https://openalex.org/W2945869148","https://openalex.org/W2398781203","https://openalex.org/W2009279505","https://openalex.org/W4206503171","https://openalex.org/W4366711670","https://openalex.org/W2972216353","https://openalex.org/W3203997580"],"abstract_inverted_index":{"Estimating":[0],"similarity":[1,17,23,96,108,166,190],"between":[2,97,104],"streaming":[3,41,137,174,202],"sets":[4,83,138],"is":[5,198],"a":[6,32,40,69,89,162,181,201],"fundamental":[7],"problem":[8,151],"with":[9,134,161,192,210],"many":[10,111],"Internet":[11],"applications,":[12],"such":[13,117],"as":[14,68,118],"evaluating":[15],"user":[16],"in":[18,28,39,74],"social":[19],"networks":[20],"and":[21,43,107,124,129,158,219,239],"analyzing":[22],"of":[24,59,80,100,143,207,231],"IP":[25],"hosts'":[26],"behaviors":[27],"communication":[29],"networks.":[30],"For":[31],"\u201cstreaming\u201d":[33],"data":[34,63,82],"set,":[35],"its":[36,51,165],"elements":[37],"arrive":[38],"fashion,":[42],"we":[44,179],"have":[45,114],"only":[46],"limited":[47],"memory":[48,105,194],"to":[49,88,92,132,199,221],"process":[50],"element":[52],"stream.":[53],"To":[54,102],"meet":[55],"the":[56,75,78,94,141,149,154,228],"size":[57],"constraint":[58],"high-speed":[60],"memory,":[61],"this":[62,177],"set":[64,203],"must":[65],"be":[66,85],"stored":[67],"summary":[70],"called":[71],"`sketch'.":[72],"Then,":[73],"distributed":[76],"scenario,":[77],"sketches":[79,209],"all":[81],"can":[84],"efficiently":[86],"transferred":[87],"central":[90],"server":[91],"calculate":[93],"Jaccard":[95],"each":[98],"pair":[99],"sets.":[101,175],"balance":[103],"cost":[106],"evaluation":[109,167],"accuracy,":[110],"sketching":[112],"methods":[113],"been":[115],"proposed,":[116],"MinHash,":[119],"virtual":[120],"odd":[121,155,183,208],"sketch":[122,156,184],"(VOS)":[123],"MaxLogHash.":[125],"However,":[126],"both":[127,217],"MinHash":[128,238],"MaxLogHash":[130],"fail":[131],"deal":[133],"fully":[135],"dynamic":[136],"that":[139,227],"allow":[140],"deletion":[142,150],"elements.":[144],"Although":[145],"VOS":[146],"partially":[147],"solves":[148],"by":[152],"adopting":[153],"structure":[157],"enhance":[159],"it":[160],"physical-virtual":[163],"structure,":[164],"accuracy":[168,230],"will":[169],"degrade":[170],"when":[171],"handling":[172],"small":[173],"In":[176],"paper,":[178],"propose":[180],"multi-resolution":[182],"(MROS),":[185],"which":[186],"allows":[187],"more":[188],"accurate":[189],"estimation":[191,229],"less":[193],"consumption.":[195],"Its":[196],"design":[197],"encode":[200],"into":[204],"multiple":[205],"layers":[206],"exponentially":[211],"reducing":[212],"sampling":[213],"probabilities.":[214],"We":[215],"conduct":[216],"experiments":[218],"analysis":[220],"evaluate":[222],"our":[223,232],"method.":[224],"Results":[225],"show":[226],"MROS":[233],"outperforms":[234],"existing":[235],"works,":[236],"e.g.,":[237],"VOS.":[240]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}