{"id":"https://openalex.org/W1984291101","doi":"https://doi.org/10.1109/hpec.2015.7322459","title":"Using a Power Law distribution to describe big data","display_name":"Using a Power Law distribution to describe big data","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W1984291101","doi":"https://doi.org/10.1109/hpec.2015.7322459","mag":"1984291101"},"language":"en","primary_location":{"id":"doi:10.1109/hpec.2015.7322459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec.2015.7322459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1509.00504","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043450560","display_name":"Vijay Gadepally","orcid":"https://orcid.org/0000-0002-4598-2808"},"institutions":[{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]},{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Vijay Gadepally","raw_affiliation_strings":["MIT Lincoln Laboratory, Lexington, MA","MIT Lincoln Laboratory, Lexington, 02420, United States"],"affiliations":[{"raw_affiliation_string":"MIT Lincoln Laboratory, Lexington, MA","institution_ids":["https://openalex.org/I4210122954"]},{"raw_affiliation_string":"MIT Lincoln Laboratory, Lexington, 02420, United States","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072108599","display_name":"Jeremy Kepner","orcid":"https://orcid.org/0000-0001-9668-2613"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]},{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeremy Kepner","raw_affiliation_strings":["MIT Lincoln Laboratory, Lexington, MA","MIT Lincoln Laboratory, Lexington, 02420, United States"],"affiliations":[{"raw_affiliation_string":"MIT Lincoln Laboratory, Lexington, MA","institution_ids":["https://openalex.org/I4210122954"]},{"raw_affiliation_string":"MIT Lincoln Laboratory, Lexington, 02420, United States","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5043450560"],"corresponding_institution_ids":["https://openalex.org/I4210122954","https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":3.8478,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.93311688,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/big-data","display_name":"Big data","score":0.8285586833953857},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.762151837348938},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6051586866378784},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5708795189857483},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5452263355255127},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5033008456230164},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.496098130941391},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4866264760494232},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.44874873757362366},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.4354196786880493},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.43193119764328003},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33131834864616394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20492711663246155},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.18870240449905396},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.17017006874084473},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0842510461807251}],"concepts":[{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.8285586833953857},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.762151837348938},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6051586866378784},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5708795189857483},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5452263355255127},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5033008456230164},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.496098130941391},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4866264760494232},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.44874873757362366},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.4354196786880493},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43193119764328003},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33131834864616394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20492711663246155},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.18870240449905396},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.17017006874084473},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0842510461807251},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/hpec.2015.7322459","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec.2015.7322459","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1509.00504","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1509.00504","pdf_url":"https://arxiv.org/pdf/1509.00504","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1509.00504","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1509.00504","pdf_url":"https://arxiv.org/pdf/1509.00504","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1982516027","https://openalex.org/W1990488619","https://openalex.org/W1993803315","https://openalex.org/W2000042664","https://openalex.org/W2025701811","https://openalex.org/W2027963417","https://openalex.org/W2048006137","https://openalex.org/W2089465933","https://openalex.org/W2114827335","https://openalex.org/W2140849606","https://openalex.org/W2146223937","https://openalex.org/W2159491186","https://openalex.org/W2168332560","https://openalex.org/W2267835966","https://openalex.org/W2950627632","https://openalex.org/W3101452997","https://openalex.org/W3102499167","https://openalex.org/W3103362336","https://openalex.org/W6681654339","https://openalex.org/W6693772185"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W4394895745","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2910064364","https://openalex.org/W4200136508","https://openalex.org/W2499527417"],"abstract_inverted_index":{"The":[0],"gap":[1],"between":[2],"data":[3,25,47,72],"production":[4],"and":[5,11,28,55,81,122,159],"user":[6],"ability":[7],"to":[8,38,117,142,163],"access,":[9],"compute":[10,123],"produce":[12,71],"meaningful":[13],"results":[14],"calls":[15],"for":[16,157],"tools":[17],"that":[18,102,130],"address":[19],"the":[20,32,36,144],"challenges":[21],"associated":[22],"with":[23,165],"big":[24,166],"volume,":[26],"velocity":[27],"variety.":[29],"One":[30],"of":[31,64,91,108,146],"key":[33],"hurdles":[34],"is":[35],"inability":[37],"methodically":[39],"remove":[40],"expected":[41],"or":[42,68,151],"uninteresting":[43,62],"elements":[44],"from":[45],"large":[46,106],"sets.":[48],"This":[49,137],"difficulty":[50],"often":[51],"wastes":[52],"valuable":[53],"researcher":[54],"computational":[56],"time":[57],"by":[58],"expending":[59],"resources":[60],"on":[61,74,134],"parts":[63],"data.":[65,109,167],"Social":[66],"sensors,":[67],"sensors":[69],"which":[70,87],"based":[73],"human":[75],"activity,":[76],"such":[77],"as":[78,92],"Wikipedia,":[79],"Twitter,":[80],"Facebook":[82],"have":[83],"an":[84,119],"underlying":[85],"structure":[86],"can":[88,139,160],"be":[89,140,161],"thought":[90],"having":[93],"a":[94,99,115,124,148],"Power":[95],"Law":[96],"distribution.":[97],"Such":[98],"distribution":[100],"implies":[101],"few":[103],"nodes":[104,156],"generate":[105],"amounts":[107],"In":[110],"this":[111],"article,":[112],"we":[113],"propose":[114],"technique":[116],"take":[118],"arbitrary":[120],"dataset":[121],"power":[125,149],"law":[126,150],"distributed":[127],"background":[128],"model":[129,138],"bases":[131],"its":[132],"parameters":[133],"observed":[135],"statistics.":[136],"used":[141],"determine":[143],"suitability":[145],"using":[147],"automatically":[152],"identify":[153],"high":[154],"degree":[155],"filtering":[158],"scaled":[162],"work":[164]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":6}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
