{"id":"https://openalex.org/W2247688741","doi":"https://doi.org/10.1109/fskd.2015.7382081","title":"Fuzzy rule-based analysis of spatio-temporal ATM usage data for fraud detection and prevention","display_name":"Fuzzy rule-based analysis of spatio-temporal ATM usage data for fraud detection and prevention","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2247688741","doi":"https://doi.org/10.1109/fskd.2015.7382081","mag":"2247688741"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2015.7382081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2015.7382081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","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/A5006375697","display_name":"Bet\u00fcl Ekizo\u011flu","orcid":null},"institutions":[{"id":"https://openalex.org/I103703290","display_name":"Sakarya University","ror":"https://ror.org/04ttnw109","country_code":"TR","type":"education","lineage":["https://openalex.org/I103703290"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Betul Ekizoglu","raw_affiliation_strings":["Department of Industrial Engineering, Sakarya University, Sakarya, TURKEY"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Sakarya University, Sakarya, TURKEY","institution_ids":["https://openalex.org/I103703290"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029134118","display_name":"Ayhan Demiriz","orcid":"https://orcid.org/0000-0002-5731-3134"},"institutions":[{"id":"https://openalex.org/I103703290","display_name":"Sakarya University","ror":"https://ror.org/04ttnw109","country_code":"TR","type":"education","lineage":["https://openalex.org/I103703290"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ayhan Demiriz","raw_affiliation_strings":["Department of Industrial Engineering, Sakarya University, Sakarya, TURKEY"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Sakarya University, Sakarya, TURKEY","institution_ids":["https://openalex.org/I103703290"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006375697"],"corresponding_institution_ids":["https://openalex.org/I103703290"],"apc_list":null,"apc_paid":null,"fwci":2.9978,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.93266631,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1009","last_page":"1014"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9776999950408936,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9760000109672546,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7886200547218323},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7523794770240784},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7522956132888794},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6722840070724487},{"id":"https://openalex.org/keywords/transaction-data","display_name":"Transaction data","score":0.6062066555023193},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.5795876979827881},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5601821541786194},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41213637590408325},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.33173805475234985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3126552104949951}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7886200547218323},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7523794770240784},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7522956132888794},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6722840070724487},{"id":"https://openalex.org/C127722929","wikidata":"https://www.wikidata.org/wiki/Q7833714","display_name":"Transaction data","level":3,"score":0.6062066555023193},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.5795876979827881},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5601821541786194},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41213637590408325},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.33173805475234985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3126552104949951}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2015.7382081","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2015.7382081","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7799999713897705,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W181063019","https://openalex.org/W1975761042","https://openalex.org/W1995450389","https://openalex.org/W2053629191","https://openalex.org/W2097958165","https://openalex.org/W2148564274","https://openalex.org/W2150299397","https://openalex.org/W2152767746","https://openalex.org/W2316613205","https://openalex.org/W6607300811"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729","https://openalex.org/W2989589039","https://openalex.org/W3007554386","https://openalex.org/W2780247929","https://openalex.org/W3108131348"],"abstract_inverted_index":{"We":[0,38,127,146,165],"present":[1,167],"a":[2,27,142,150,185],"novel":[3],"approach":[4],"for":[5],"detecting":[6],"fraudulent":[7],"behaviors":[8],"from":[9,74,176],"automated":[10],"teller":[11],"machine":[12],"(ATM)":[13],"usage":[14,130],"data":[15,66,73,85,180],"by":[16,59,70,141,181],"analyzing":[17],"geo-behavioral":[18],"habits":[19],"of":[20,26,32,44,61,97,138,153,161,183],"the":[21,24,41,75,79,83,111,159],"customers":[22],"describe":[23],"use":[25,103],"fuzzy":[28,116,186],"rule-based":[29,187],"system":[30],"capable":[31],"classifying":[33],"suspicious":[34],"and":[35],"non-suspicious":[36],"transactions.":[37],"first":[39],"compute":[40],"geographic":[42],"entropies":[43],"ATM":[45,55,129,154,178],"cardholders":[46],"to":[47,78,107,124],"form":[48],"customer":[49],"classes":[50],"based":[51],"on":[52],"these":[53],"entropies.":[54],"transactions":[56],"are":[57,86],"spatio-temporal":[58],"inclusion":[60],"location":[62,77],"information.":[63],"The":[64],"transition":[65,84,112],"can":[67,92,101,119,173],"be":[68,93,122,174],"generated":[69],"using":[71,184],"transaction":[72,179],"current":[76],"next":[80],"one.":[81],"Once,":[82],"generated,":[87],"statistical":[88],"outlier":[89],"detection":[90],"techniques":[91],"utilized.":[94],"On":[95],"top":[96],"classical":[98],"methods,":[99],"we":[100],"easily":[102,121],"crisp":[104],"unsupervised":[105],"methods":[106],"detect":[108],"outliers":[109],"in":[110],"data.":[113],"In":[114],"addition,":[115],"C-Means":[117],"algorithm":[118],"also":[120,166],"implemented":[123],"determine":[125],"outliers.":[126],"analyze":[128],"dataset":[131],"which":[132],"contains":[133],"around":[134],"two":[135],"years'":[136],"worth":[137],"data,":[139],"provided":[140],"mid-size":[143],"Turkish":[144],"bank.":[145],"have":[147],"shown":[148],"that":[149,172],"significant":[151],"bulk":[152],"users":[155],"does":[156],"not":[157],"leave":[158],"vicinity":[160],"their":[162],"living":[163],"places.":[164],"some":[168],"insightful":[169],"business":[170],"rules":[171],"extracted":[175],"geo-tagged":[177],"means":[182],"system.":[188]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
