{"id":"https://openalex.org/W2494094521","doi":"https://doi.org/10.1109/smartcomp.2016.7501694","title":"Health Care Fraud Detection with Community Detection Algorithms","display_name":"Health Care Fraud Detection with Community Detection Algorithms","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2494094521","doi":"https://doi.org/10.1109/smartcomp.2016.7501694","mag":"2494094521"},"language":"en","primary_location":{"id":"doi:10.1109/smartcomp.2016.7501694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartcomp.2016.7501694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Smart Computing (SMARTCOMP)","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/A5051208435","display_name":"Aryya Gangopadhyay","orcid":"https://orcid.org/0000-0002-7553-7932"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Aryya Gangopadhyay","raw_affiliation_strings":["Inf. Syst. Univ. of Maryland Baltimore County, MD, USA"],"affiliations":[{"raw_affiliation_string":"Inf. Syst. Univ. of Maryland Baltimore County, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101598289","display_name":"Song Chen","orcid":"https://orcid.org/0000-0001-9401-3010"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song Chen","raw_affiliation_strings":["Information Systems University of Maryland, Baltimor County"],"affiliations":[{"raw_affiliation_string":"Information Systems University of Maryland, Baltimor County","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051208435"],"corresponding_institution_ids":["https://openalex.org/I79272384"],"apc_list":null,"apc_paid":null,"fwci":1.7139,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.88935554,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9986000061035156,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9986000061035156,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9617000222206116,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9236999750137329,"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":0.7098086476325989},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.625891923904419},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5911607146263123},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5867071747779846},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.5806146860122681},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5165756940841675},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.5033983588218689},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4806898534297943},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.46920767426490784},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46700820326805115},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4375547468662262},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4315027594566345},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32700201869010925},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08280962705612183},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07706445455551147}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7098086476325989},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.625891923904419},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5911607146263123},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5867071747779846},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.5806146860122681},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5165756940841675},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.5033983588218689},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4806898534297943},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.46920767426490784},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46700820326805115},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4375547468662262},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4315027594566345},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32700201869010925},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08280962705612183},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07706445455551147},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smartcomp.2016.7501694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartcomp.2016.7501694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Smart Computing (SMARTCOMP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7900000214576721,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W231475902","https://openalex.org/W1999786079","https://openalex.org/W2127048411","https://openalex.org/W2151936673","https://openalex.org/W3102641634"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W2965083567","https://openalex.org/W4235240664","https://openalex.org/W2757182831","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W97075385"],"abstract_inverted_index":{"Fraud":[0],"detection":[1,142],"is":[2],"interesting":[3],"research":[4],"topic":[5],"and":[6,31,37,53,55,67,73,83,98,109,136,154],"it":[7],"not":[8],"only":[9],"needs":[10,16],"data":[11],"mining":[12],"techniques":[13],"but":[14,77],"also":[15],"a":[17,118],"lot":[18],"of":[19,71,120,160],"inputs":[20],"from":[21],"domain":[22],"experts.":[23],"In":[24,62],"health":[25,87,132],"care":[26,88,133],"claims,":[27],"relationships":[28,72,79],"between":[29],"physicians":[30,52],"patients":[32,54],"form":[33],"complex":[34],"communities":[35,39,158],"structures":[36,159],"these":[38,96,115,149],"could":[40],"lead":[41],"to":[42,57,94,106,128,138],"potential":[43,86],"fraud":[44,141],"discoveries.":[45],"Traditionally,":[46],"researchers":[47],"have":[48],"focused":[49],"on":[50,75],"clustering":[51],"tried":[56],"find":[58],"the":[59,130,140,148,157],"suspicious":[60,82],"communities.":[61,100],"this":[63],"paper,":[64],"we":[65],"studied":[66],"discussed":[68],"different":[69],"types":[70],"focus":[74],"small":[76,97],"exclusive":[78,99],"that":[80],"are":[81,110,151],"may":[84],"indicate":[85],"frauds.":[89],"We":[90,113],"developed":[91],"two":[92],"algorithms":[93,102,116,150],"detect":[95],"These":[101,123],"can":[103,155],"be":[104],"applied":[105],"larger":[107],"dataset":[108],"highly":[111],"scalable.":[112],"tested":[114],"with":[117],"set":[119],"synthesized":[121,124],"datasets.":[122],"datasets":[125,135],"were":[126],"created":[127],"resemble":[129],"real":[131],"claims":[134],"used":[137],"test":[139,145],"algorithms.":[143],"The":[144],"results":[146],"show":[147],"very":[152],"efficient":[153],"evaluate":[156],"50,000":[161],"providers":[162],"in":[163],"about":[164],"1":[165],"minute.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
