{"id":"https://openalex.org/W2153387921","doi":"https://doi.org/10.1145/1081870.1081922","title":"Using relational knowledge discovery to prevent securities fraud","display_name":"Using relational knowledge discovery to prevent securities fraud","publication_year":2005,"publication_date":"2005-08-21","ids":{"openalex":"https://openalex.org/W2153387921","doi":"https://doi.org/10.1145/1081870.1081922","mag":"2153387921"},"language":"en","primary_location":{"id":"doi:10.1145/1081870.1081922","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1081870.1081922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining","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/A5064439579","display_name":"Jennifer Neville","orcid":"https://orcid.org/0000-0001-8108-4899"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jennifer Neville","raw_affiliation_strings":["University of Massachusetts - Amherst, Amherst, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts - Amherst, Amherst, MA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079000862","display_name":"\u00d6zg\u00fcr \u015eim\u015fek","orcid":"https://orcid.org/0000-0001-5449-0437"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"\u00d6zg\u00fcr \u015eim\u015fek","raw_affiliation_strings":["University of Massachusetts - Amherst, Amherst, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts - Amherst, Amherst, MA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006681132","display_name":"David Jensen","orcid":"https://orcid.org/0000-0001-5653-3349"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Jensen","raw_affiliation_strings":["University of Massachusetts - Amherst, Amherst, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts - Amherst, Amherst, MA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060864308","display_name":"John Komoroske","orcid":null},"institutions":[{"id":"https://openalex.org/I4210147877","display_name":"Nasdaq (United States)","ror":"https://ror.org/04mcweq87","country_code":"US","type":"company","lineage":["https://openalex.org/I4210147877"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Komoroske","raw_affiliation_strings":["National Association of Securities Dealers, Washington, DC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Association of Securities Dealers, Washington, DC","institution_ids":["https://openalex.org/I4210147877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112198408","display_name":"Kelly Nicole Brunson Palmer","orcid":null},"institutions":[{"id":"https://openalex.org/I4210147877","display_name":"Nasdaq (United States)","ror":"https://ror.org/04mcweq87","country_code":"US","type":"company","lineage":["https://openalex.org/I4210147877"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kelly Palmer","raw_affiliation_strings":["National Association of Securities Dealers, Washington, DC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Association of Securities Dealers, Washington, DC","institution_ids":["https://openalex.org/I4210147877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039188546","display_name":"Henry G. Goldberg","orcid":null},"institutions":[{"id":"https://openalex.org/I4210147877","display_name":"Nasdaq (United States)","ror":"https://ror.org/04mcweq87","country_code":"US","type":"company","lineage":["https://openalex.org/I4210147877"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Henry Goldberg","raw_affiliation_strings":["National Association of Securities Dealers, Washington, DC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Association of Securities Dealers, Washington, DC","institution_ids":["https://openalex.org/I4210147877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.7292,"has_fulltext":false,"cited_by_count":113,"citation_normalized_percentile":{"value":0.97699741,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"449","last_page":"458"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9613999724388123,"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":0.9613999724388123,"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/T11838","display_name":"Crime, Illicit Activities, and Governance","score":0.9509999752044678,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T13643","display_name":"Artificial Intelligence in Law","score":0.9210000038146973,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/commit","display_name":"Commit","score":0.8050122857093811},{"id":"https://openalex.org/keywords/securities-fraud","display_name":"Securities fraud","score":0.7100164294242859},{"id":"https://openalex.org/keywords/misconduct","display_name":"Misconduct","score":0.6373026371002197},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.48111289739608765},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.47310614585876465},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43092668056488037},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4188055396080017},{"id":"https://openalex.org/keywords/accounting","display_name":"Accounting","score":0.39205268025398254},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3810807764530182},{"id":"https://openalex.org/keywords/actuarial-science","display_name":"Actuarial science","score":0.35183829069137573},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.3253277540206909},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.27349498867988586},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.16117307543754578},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13573917746543884},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.1067807674407959},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08983218669891357}],"concepts":[{"id":"https://openalex.org/C153180980","wikidata":"https://www.wikidata.org/wiki/Q19776675","display_name":"Commit","level":2,"score":0.8050122857093811},{"id":"https://openalex.org/C2776801101","wikidata":"https://www.wikidata.org/wiki/Q4570975","display_name":"Securities fraud","level":3,"score":0.7100164294242859},{"id":"https://openalex.org/C2780587575","wikidata":"https://www.wikidata.org/wiki/Q6875295","display_name":"Misconduct","level":2,"score":0.6373026371002197},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.48111289739608765},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.47310614585876465},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43092668056488037},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4188055396080017},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.39205268025398254},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3810807764530182},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.35183829069137573},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3253277540206909},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.27349498867988586},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.16117307543754578},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13573917746543884},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.1067807674407959},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08983218669891357},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C2778272461","wikidata":"https://www.wikidata.org/wiki/Q190752","display_name":"Supreme court","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1081870.1081922","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1081870.1081922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.377.5451","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.377.5451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.purdue.edu/homes/aliaga/cs197-10/papers/relational-knowledge.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.387.5314","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.387.5314","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.purdue.edu/homes/neville/papers/neville-et-al-tr0523.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310173","display_name":"University of Massachusetts","ror":"https://ror.org/0072zz521"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W65085810","https://openalex.org/W330951725","https://openalex.org/W1482003017","https://openalex.org/W1509515766","https://openalex.org/W1517113043","https://openalex.org/W1554944419","https://openalex.org/W1559400719","https://openalex.org/W1666347389","https://openalex.org/W1933130724","https://openalex.org/W2028137574","https://openalex.org/W2035703056","https://openalex.org/W2076008912","https://openalex.org/W2123827533","https://openalex.org/W2126185296","https://openalex.org/W2140127353","https://openalex.org/W2163598528","https://openalex.org/W2170913656","https://openalex.org/W2962735828","https://openalex.org/W3112180085","https://openalex.org/W4206727053"],"related_works":["https://openalex.org/W4367365664","https://openalex.org/W4385326140","https://openalex.org/W4293227618","https://openalex.org/W2136634148","https://openalex.org/W3122851392","https://openalex.org/W3122800671","https://openalex.org/W4250708772","https://openalex.org/W4288862737","https://openalex.org/W1984769753","https://openalex.org/W3026125430"],"abstract_inverted_index":{"We":[0],"describe":[1],"an":[2,117],"application":[3],"of":[4,13,17,84,125,138,154],"relational":[5,63],"knowledge":[6],"discovery":[7],"to":[8,42,56,74,116,147],"a":[9,81],"key":[10],"regulatory":[11,47],"mission":[12],"the":[14,23,50,75,88,129,151,172],"National":[15],"Association":[16],"Securities":[18],"Dealers":[19],"(NASD).":[20],"NASD":[21,141,156],"is":[22],"world&amp;apos;s":[24],"largest":[25],"privatesector":[26],"securities":[27,37,59,85],"regulator,":[28],"with":[29,72,150],"responsibility":[30],"for":[31],"preventing":[32],"and":[33,132],"discovering":[34],"misconduct":[35],"among":[36,96],"brokers.":[38],"Our":[39,91],"goal":[40],"was":[41],"help":[43],"focus":[44],"NASD\u2019s":[45],"limited":[46],"resources":[48],"on":[49],"brokers":[51,71,97],"who":[52],"are":[53,176],"most":[54],"likely":[55],"engage":[57],"in":[58,87,159,178],"violations.":[60],"Using":[61],"statistical":[62],"learning":[64],"algorithms,":[65],"we":[66],"developed":[67],"models":[68,92,113,164],"that":[69,77,175],"rank":[70],"respect":[73],"probability":[76],"they":[78],"would":[79],"commit":[80],"serious":[82],"violation":[83],"regulations":[86],"near":[89],"future.":[90],"incorporate":[93],"organizational":[94],"relationships":[95],"(e.g.,":[98],"past":[99],"coworker),":[100],"which":[101],"domain":[102],"experts":[103],"consider":[104],"important":[105],"but":[106],"cannot":[107],"easily":[108],"use":[109,179],"otherwise.":[110],"The":[111],"learned":[112],"were":[114,145],"subjected":[115],"extensive":[118],"evaluation":[119],"using":[120],"more":[121],"than":[122,171],"18":[123],"months":[124],"data":[126],"unseen":[127],"by":[128,140],"model":[130],"developers":[131],"comprising":[133],"over":[134],"two":[135],"person":[136],"weeks":[137],"effort":[139],"staff.":[142],"Model":[143],"predictions":[144],"found":[146],"correlate":[148],"highly":[149],"subjective":[152],"evaluations":[153],"experienced":[155],"examiners.":[157],"Furthermore,":[158],"all":[160],"performance":[161],"measures,":[162],"our":[163],"performed":[165],"as":[166,168],"well":[167],"or":[169],"better":[170],"handcrafted":[173],"rules":[174],"currently":[177],"at":[180],"NASD.":[181],"1.":[182]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":15},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":12}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
