{"id":"https://openalex.org/W2066497609","doi":"https://doi.org/10.1109/sadfe.2013.6911549","title":"MapReduce-based frequent itemset mining for analysis of electronic evidence","display_name":"MapReduce-based frequent itemset mining for analysis of electronic evidence","publication_year":2013,"publication_date":"2013-11-01","ids":{"openalex":"https://openalex.org/W2066497609","doi":"https://doi.org/10.1109/sadfe.2013.6911549","mag":"2066497609"},"language":"en","primary_location":{"id":"doi:10.1109/sadfe.2013.6911549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sadfe.2013.6911549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 8th International Workshop on Systematic Approaches to Digital Forensics Engineering (SADFE)","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/A5110695155","display_name":"Xueqing Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xueqing Jiang","raw_affiliation_strings":["College of Computer, Nanjing University of Posts & Telecommunications, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, Nanjing University of Posts & Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021136987","display_name":"Guozi Sun","orcid":"https://orcid.org/0000-0003-1888-7001"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guozi Sun","raw_affiliation_strings":["College of Computer, Nanjing University of Posts & Telecommunications, Nanjing, China","Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer, Nanjing University of Posts & Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5110695155"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":0.8089,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.82606308,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"50","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9997000098228455,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9997000098228455,"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/T11652","display_name":"Imbalanced Data Classification 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/T12034","display_name":"Digital and Cyber Forensics","score":0.9846000075340271,"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":0.7964228391647339},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.7522203922271729},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7300792932510376},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6650786399841309},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4640820026397705},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.46371057629585266},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4438306391239166},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.413848876953125},{"id":"https://openalex.org/keywords/gsp-algorithm","display_name":"GSP Algorithm","score":0.4119229018688202},{"id":"https://openalex.org/keywords/apriori-algorithm","display_name":"Apriori algorithm","score":0.27988940477371216}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7964228391647339},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.7522203922271729},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7300792932510376},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6650786399841309},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4640820026397705},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.46371057629585266},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4438306391239166},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.413848876953125},{"id":"https://openalex.org/C87146676","wikidata":"https://www.wikidata.org/wiki/Q5514602","display_name":"GSP Algorithm","level":4,"score":0.4119229018688202},{"id":"https://openalex.org/C81440476","wikidata":"https://www.wikidata.org/wiki/Q513511","display_name":"Apriori algorithm","level":3,"score":0.27988940477371216},{"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/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sadfe.2013.6911549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sadfe.2013.6911549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 8th International Workshop on Systematic Approaches to Digital Forensics Engineering (SADFE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"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":18,"referenced_works":["https://openalex.org/W69176377","https://openalex.org/W1500436346","https://openalex.org/W2004807963","https://openalex.org/W2006132208","https://openalex.org/W2032469362","https://openalex.org/W2056910091","https://openalex.org/W2080135463","https://openalex.org/W2108082862","https://openalex.org/W2109722477","https://openalex.org/W2156350103","https://openalex.org/W2166559705","https://openalex.org/W2173213060","https://openalex.org/W2181713745","https://openalex.org/W2327759298","https://openalex.org/W2542364126","https://openalex.org/W4252403066","https://openalex.org/W6676367512","https://openalex.org/W6685614191"],"related_works":["https://openalex.org/W2106878563","https://openalex.org/W2376949134","https://openalex.org/W3034345083","https://openalex.org/W1483188779","https://openalex.org/W2157620887","https://openalex.org/W2348452205","https://openalex.org/W4389611318","https://openalex.org/W2383811731","https://openalex.org/W2981042271","https://openalex.org/W2390733913"],"abstract_inverted_index":{"Association":[0],"rules":[1,16],"can":[2,31,107],"mine":[3,22],"the":[4,11,69,79,82,90,98,125,134,140,148,152,190,206,214,219],"relevant":[5],"evidence":[6,64,129],"of":[7,84,92,97,127,136,147,218],"computer":[8],"crime":[9,23,38],"from":[10],"massive":[12],"data":[13,18,58,80,202],"and":[14,20,25,36,41,55,86,203,208,216],"association":[15],"among":[17,27],"itemset,":[19],"further":[21],"trends":[24],"connections":[26],"different":[28],"crimes.":[29],"They":[30],"help":[32],"polices":[33],"detect":[34],"case":[35],"prevent":[37],"with":[39,200],"clues":[40],"criterions.":[42],"Frequent":[43],"itemset":[44],"mining":[45,52,59,94,103,110],"(FIM)":[46],"plays":[47],"a":[48,112,160,182],"fundamental":[49],"role":[50],"in":[51,173,177],"associations,":[53],"correlations":[54],"many":[56],"real-world":[57],"fields":[60],"such":[61],"as":[62],"electronic":[63,128],"analysis":[65,126],"area.":[66,175],"FP-growth":[67,93],"is":[68,195],"most":[70],"famous":[71],"FIM":[72],"algorithm":[73,123,185],"for":[74,115,169],"discovering":[75],"frequent":[76,101,153],"patterns.":[77],"As":[78],"incrementing,":[81],"cost":[83],"time":[85],"space":[87],"will":[88,132],"be":[89,211],"bottleneck":[91],"algorithms.":[95],"One":[96],"existing":[99],"incremental":[100,109,116],"pattern":[102],"algorithms":[104,165],"called":[105,186],"SPO-tree":[106],"perform":[108],"by":[111],"single":[113],"scan":[114],"mining.":[117],"But":[118],"how":[119],"to":[120,124,151,156,198,210,213,222],"apply":[121],"this":[122,137,170,178],"more":[130],"effectively":[131],"become":[133],"focus":[135],"paper.":[138],"In":[139],"past":[141,164],"research,":[142],"little":[143,161],"people":[144],"take":[145],"care":[146],"item":[149,154],"mined":[150],"needing":[155],"update":[157],"or":[158],"inserted":[159],"data.":[162],"The":[163],"are":[166],"not":[167],"suit":[168],"problem":[171],"especially":[172],"forensic":[174],"So,":[176],"paper,":[179],"we":[180],"propose":[181],"novel":[183],"parallelized":[184],"PISPO":[187],"based":[188],"on":[189],"cloud-computing":[191],"framework":[192],"MapReduce,":[193],"which":[194],"widely":[196],"used":[197],"cope":[199],"large-scale":[201],"captures":[204],"both":[205],"content":[207],"state":[209],"distributed":[212],"changed":[215],"original":[217],"transactions":[220],"dataset":[221],"SPO-tree.":[223]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}