{"id":"https://openalex.org/W2910109950","doi":"https://doi.org/10.1007/978-3-030-10997-4_23","title":"Solving the False Positives Problem in Fraud Prediction Using Automated Feature Engineering","display_name":"Solving the False Positives Problem in Fraud Prediction Using Automated Feature Engineering","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2910109950","doi":"https://doi.org/10.1007/978-3-030-10997-4_23","mag":"2910109950"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-030-10997-4_23","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-030-10997-4_23","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"conference-paper","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/A5038619486","display_name":"Roy Wedge","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roy Wedge","raw_affiliation_strings":["Data to AI Lab, LIDS, MIT, Cambridge, MA, 02139, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data to AI Lab, LIDS, MIT, Cambridge, MA, 02139, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070222452","display_name":"James Max Kanter","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"James Max Kanter","raw_affiliation_strings":["Data to AI Lab, LIDS, MIT, Cambridge, MA, 02139, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data to AI Lab, LIDS, MIT, Cambridge, MA, 02139, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067352490","display_name":"Kalyan Veeramachaneni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kalyan Veeramachaneni","raw_affiliation_strings":["Data to AI Lab, LIDS, MIT, Cambridge, MA, 02139, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data to AI Lab, LIDS, MIT, Cambridge, MA, 02139, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056294504","display_name":"Santiago Moral Rubio","orcid":null},"institutions":[{"id":"https://openalex.org/I133498377","display_name":"Banco Bilbao Vizcaya Argentaria (Spain)","ror":"https://ror.org/0537dnd74","country_code":"ES","type":"company","lineage":["https://openalex.org/I133498377"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Santiago Moral Rubio","raw_affiliation_strings":["Banco Bilbao Vizcaya Argentaria (BBVA), Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Banco Bilbao Vizcaya Argentaria (BBVA), Madrid, Spain","institution_ids":["https://openalex.org/I133498377"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015115781","display_name":"Sergio Iglesias P\u00e9rez","orcid":"https://orcid.org/0000-0003-2994-6281"},"institutions":[{"id":"https://openalex.org/I133498377","display_name":"Banco Bilbao Vizcaya Argentaria (Spain)","ror":"https://ror.org/0537dnd74","country_code":"ES","type":"company","lineage":["https://openalex.org/I133498377"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Sergio Iglesias Perez","raw_affiliation_strings":["Banco Bilbao Vizcaya Argentaria (BBVA), Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Banco Bilbao Vizcaya Argentaria (BBVA), Madrid, Spain","institution_ids":["https://openalex.org/I133498377"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5070222452"],"corresponding_institution_ids":[],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":1.4213,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.86665621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"372","last_page":"388"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9916999936103821,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9898999929428101,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8131344318389893},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.8119250535964966},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.6911320686340332},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.5672659873962402},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5504874587059021},{"id":"https://openalex.org/keywords/credit-card-fraud","display_name":"Credit card fraud","score":0.5351250171661377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5189254283905029},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5174270868301392},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5117597579956055},{"id":"https://openalex.org/keywords/euros","display_name":"Euros","score":0.4963453412055969},{"id":"https://openalex.org/keywords/credit-card","display_name":"Credit card","score":0.4784376919269562},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.461490273475647},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41992321610450745},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.406028687953949},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.18829160928726196},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.15035516023635864},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.1358460783958435}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8131344318389893},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.8119250535964966},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.6911320686340332},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.5672659873962402},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5504874587059021},{"id":"https://openalex.org/C2780747020","wikidata":"https://www.wikidata.org/wiki/Q83873","display_name":"Credit card fraud","level":4,"score":0.5351250171661377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5189254283905029},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5174270868301392},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5117597579956055},{"id":"https://openalex.org/C2778097690","wikidata":"https://www.wikidata.org/wiki/Q5413797","display_name":"Euros","level":2,"score":0.4963453412055969},{"id":"https://openalex.org/C2983355114","wikidata":"https://www.wikidata.org/wiki/Q161380","display_name":"Credit card","level":3,"score":0.4784376919269562},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.461490273475647},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41992321610450745},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.406028687953949},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.18829160928726196},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15035516023635864},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.1358460783958435},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C15708023","wikidata":"https://www.wikidata.org/wiki/Q80083","display_name":"Humanities","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-030-10997-4_23","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-030-10997-4_23","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1964089535","https://openalex.org/W1966493433","https://openalex.org/W2045049630","https://openalex.org/W2074346829","https://openalex.org/W2105809068","https://openalex.org/W2122025464","https://openalex.org/W2160150610","https://openalex.org/W2161336914","https://openalex.org/W2182353144","https://openalex.org/W2405680064","https://openalex.org/W2751596245","https://openalex.org/W3099128122"],"related_works":["https://openalex.org/W2483711049","https://openalex.org/W4224237387","https://openalex.org/W3150316110","https://openalex.org/W4313247660","https://openalex.org/W3153799676","https://openalex.org/W2984276143","https://openalex.org/W4281702918","https://openalex.org/W4283392145","https://openalex.org/W3111672143","https://openalex.org/W2942788488"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2019,"cited_by_count":1}],"updated_date":"2026-08-04T08:18:43.703281","created_date":"2025-10-10T00:00:00"}
