{"id":"https://openalex.org/W4239270184","doi":"https://doi.org/10.1109/asonam.2016.7752351","title":"Frequent and non-frequent pattern detection in big data streams: An experimental simulation in 1 trillion data points","display_name":"Frequent and non-frequent pattern detection in big data streams: An experimental simulation in 1 trillion data points","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W4239270184","doi":"https://doi.org/10.1109/asonam.2016.7752351"},"language":"en","primary_location":{"id":"doi:10.1109/asonam.2016.7752351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2016.7752351","pdf_url":null,"source":{"id":"https://openalex.org/S4363608003","display_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","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/A5083041537","display_name":"Konstantinos F. Xylogiannopoulos","orcid":"https://orcid.org/0000-0003-2376-898X"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Konstantinos F. Xylogiannopoulos","raw_affiliation_strings":["Dept. of Computer Science, University of Calgary, Calgary, Alberta, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, University of Calgary, Calgary, Alberta, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066265052","display_name":"Reda Alhajj","orcid":"https://orcid.org/0000-0001-6657-9738"},"institutions":[{"id":"https://openalex.org/I2802113776","display_name":"Hellenic Air Force","ror":"https://ror.org/044xk2674","country_code":"GR","type":"government","lineage":["https://openalex.org/I2802113776"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Reda Alhajj","raw_affiliation_strings":["Dept. of Informatics and Computers, Hellenic Air Force Academy, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Informatics and Computers, Hellenic Air Force Academy, Greece","institution_ids":["https://openalex.org/I2802113776"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034281379","display_name":"Panagiotis Karampelas","orcid":"https://orcid.org/0000-0003-1684-7612"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Panagiotis Karampelas","raw_affiliation_strings":["Dept. of Computer Science, University of Calgary, Calgary, Alberta, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, University of Calgary, Calgary, Alberta, Canada","institution_ids":["https://openalex.org/I168635309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1941,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56730212,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"8","issue":null,"first_page":"931","last_page":"938"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","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/T11269","display_name":"Algorithms and Data Compression","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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9973000288009644,"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"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9969000220298767,"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/computer-science","display_name":"Computer science","score":0.7910821437835693},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.768065869808197},{"id":"https://openalex.org/keywords/string","display_name":"String (physics)","score":0.6493545770645142},{"id":"https://openalex.org/keywords/suffix","display_name":"Suffix","score":0.5305139422416687},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5138147473335266},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.4901019036769867},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4736408293247223},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.4517369866371155},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.444095253944397},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.206945538520813},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09604758024215698}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7910821437835693},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.768065869808197},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.6493545770645142},{"id":"https://openalex.org/C2779804580","wikidata":"https://www.wikidata.org/wiki/Q102047","display_name":"Suffix","level":2,"score":0.5305139422416687},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5138147473335266},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.4901019036769867},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4736408293247223},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.4517369866371155},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.444095253944397},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.206945538520813},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09604758024215698},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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:10.1109/asonam.2016.7752351","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2016.7752351","pdf_url":null,"source":{"id":"https://openalex.org/S4363608003","display_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W139562302","https://openalex.org/W324416766","https://openalex.org/W1553409264","https://openalex.org/W1608420182","https://openalex.org/W1675727887","https://openalex.org/W1969173824","https://openalex.org/W1971140524","https://openalex.org/W1989477967","https://openalex.org/W2024145045","https://openalex.org/W2029955663","https://openalex.org/W2049282244","https://openalex.org/W2060324268","https://openalex.org/W2064379477","https://openalex.org/W2080234606","https://openalex.org/W2090509093","https://openalex.org/W2112452856","https://openalex.org/W2113139394","https://openalex.org/W2319265692","https://openalex.org/W2533248932","https://openalex.org/W2739227211","https://openalex.org/W6621160150","https://openalex.org/W6633322224","https://openalex.org/W6636702256","https://openalex.org/W6662775348","https://openalex.org/W6665936323"],"related_works":["https://openalex.org/W2371678724","https://openalex.org/W4311055779","https://openalex.org/W2761558751","https://openalex.org/W3128574596","https://openalex.org/W2391300236","https://openalex.org/W2981728181","https://openalex.org/W2989529099","https://openalex.org/W2978475281","https://openalex.org/W2040778820","https://openalex.org/W2003608043"],"abstract_inverted_index":{"Big":[0],"data":[1,17,23,36,89,111,143,171],"streaming":[2],"analysis":[3,33],"nowadays":[4],"has":[5],"become":[6],"one":[7,138],"of":[8,16,22,34,43,55,75,100,126,139,160],"the":[9,14,28,41,59,73,109,118,124,140,158],"most":[10],"important":[11,39],"topic":[12],"in":[13,79,82,130,152],"list":[15],"analysts":[18],"since":[19],"enormous":[20],"amount":[21],"are":[24],"produced":[25],"daily":[26],"by":[27],"numerous":[29],"smart":[30],"devices.":[31],"The":[32],"such":[35],"is":[37,168],"very":[38,87],"and":[40,117],"detection":[42,74,125],"frequent":[44],"or":[45],"even":[46],"non-frequent":[47],"patterns":[48,78,129],"can":[49],"be":[50],"critical":[51],"for":[52],"many":[53],"aspects":[54],"our":[56,69,161],"lives.":[57],"In":[58],"current":[60],"paper,":[61],"we":[62,133],"propose":[63],"a":[64,80,86,131],"new":[65],"methodology":[66],"based":[67],"on":[68],"previous":[70],"work":[71],"regarding":[72],"all":[76,127],"repeated":[77,128],"string":[81,132],"order":[83],"to":[84,135,157,170],"analyze":[85,136],"big":[88],"stream":[90],"with":[91,148],"1":[92,97,101,141],"Trillion":[93],"digits,":[94],"composed":[95],"from":[96],"thousand":[98],"subsequences":[99],"billion":[102,142],"digits":[103],"each":[104,137],"one.":[105],"More":[106],"specifically,":[107],"using":[108,145],"novel":[110],"structure,":[112],"LERP":[113],"Reduced":[114],"Suffix":[115],"Array,":[116],"innovative":[119],"ARPaD":[120],"algorithm":[121],"which":[122,155,167],"allows":[123],"managed":[134],"points,":[144],"10":[146],"computers":[147],"standard":[149],"hardware":[150],"configuration,":[151],"33":[153],"minutes":[154],"outperforms":[156],"best":[159],"knowledge":[162],"any":[163],"other":[164],"existing":[165],"methodology,":[166],"equivalent":[169],"point":[172],"generation":[173],"every":[174],"2":[175],"microseconds.":[176]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
