{"id":"https://openalex.org/W2493971940","doi":"https://doi.org/10.1145/2908812.2908896","title":"Using an Ant Colony Optimization Algorithm for Monotonic Regression Rule Discovery","display_name":"Using an Ant Colony Optimization Algorithm for Monotonic Regression Rule Discovery","publication_year":2016,"publication_date":"2016-07-20","ids":{"openalex":"https://openalex.org/W2493971940","doi":"https://doi.org/10.1145/2908812.2908896","mag":"2493971940"},"language":"en","primary_location":{"id":"doi:10.1145/2908812.2908896","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2908812.2908896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference 2016","raw_type":"proceedings-article"},"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/A5046998284","display_name":"James Brookhouse","orcid":"https://orcid.org/0000-0002-9802-7070"},"institutions":[{"id":"https://openalex.org/I167056439","display_name":"Medway School of Pharmacy","ror":"https://ror.org/00fa9v295","country_code":"GB","type":"education","lineage":["https://openalex.org/I167056439"]},{"id":"https://openalex.org/I20581793","display_name":"University of Kent","ror":"https://ror.org/00xkeyj56","country_code":"GB","type":"education","lineage":["https://openalex.org/I20581793"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"James Brookhouse","raw_affiliation_strings":["University of Kent, Chatham Maritime, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kent, Chatham Maritime, United Kingdom","institution_ids":["https://openalex.org/I167056439","https://openalex.org/I20581793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065674426","display_name":"Fernando E. B. Otero","orcid":"https://orcid.org/0000-0003-2172-297X"},"institutions":[{"id":"https://openalex.org/I167056439","display_name":"Medway School of Pharmacy","ror":"https://ror.org/00fa9v295","country_code":"GB","type":"education","lineage":["https://openalex.org/I167056439"]},{"id":"https://openalex.org/I20581793","display_name":"University of Kent","ror":"https://ror.org/00xkeyj56","country_code":"GB","type":"education","lineage":["https://openalex.org/I20581793"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Fernando E.B. Otero","raw_affiliation_strings":["University of Kent, Chatham Maritime, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Kent, Chatham Maritime, United Kingdom","institution_ids":["https://openalex.org/I167056439","https://openalex.org/I20581793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7881,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.70104439,"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":"437","last_page":"444"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9968000054359436,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/monotonic-function","display_name":"Monotonic function","score":0.7319304943084717},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6906291842460632},{"id":"https://openalex.org/keywords/ordinal-regression","display_name":"Ordinal regression","score":0.4889358580112457},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4787680208683014},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46332308650016785},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43212446570396423},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.4286000430583954},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4267372786998749},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4252700209617615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42364245653152466},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18052759766578674},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06713956594467163}],"concepts":[{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.7319304943084717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6906291842460632},{"id":"https://openalex.org/C110313322","wikidata":"https://www.wikidata.org/wiki/Q7100793","display_name":"Ordinal regression","level":2,"score":0.4889358580112457},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4787680208683014},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46332308650016785},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43212446570396423},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.4286000430583954},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4267372786998749},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4252700209617615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42364245653152466},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18052759766578674},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06713956594467163},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2908812.2908896","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2908812.2908896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference 2016","raw_type":"proceedings-article"},{"id":"pmh:oai:kar.kent.ac.uk:55191","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2908812.2908896>)","pdf_url":null,"source":{"id":"https://openalex.org/S4377196264","display_name":"Kent Academic Repository (University of Kent)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I20581793","host_organization_name":"University of Kent","host_organization_lineage":["https://openalex.org/I20581793"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Conference proceeding"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.4300000071525574,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W198465000","https://openalex.org/W225325518","https://openalex.org/W604429516","https://openalex.org/W1523293200","https://openalex.org/W1573676079","https://openalex.org/W1584845053","https://openalex.org/W1593930037","https://openalex.org/W1606224365","https://openalex.org/W1769852110","https://openalex.org/W1781794689","https://openalex.org/W1971505868","https://openalex.org/W2023213888","https://openalex.org/W2036426188","https://openalex.org/W2039045151","https://openalex.org/W2040897920","https://openalex.org/W2094299830","https://openalex.org/W2125965138","https://openalex.org/W2129202132","https://openalex.org/W2142827986","https://openalex.org/W2165201864","https://openalex.org/W3023612622","https://openalex.org/W3120740533","https://openalex.org/W4248559578","https://openalex.org/W4299796063"],"related_works":["https://openalex.org/W2077314575","https://openalex.org/W4315701745","https://openalex.org/W1990290471","https://openalex.org/W4380682190","https://openalex.org/W2005710836","https://openalex.org/W3210452439","https://openalex.org/W2102386043","https://openalex.org/W2945307361","https://openalex.org/W2075768550","https://openalex.org/W2116636209"],"abstract_inverted_index":{"Many":[0],"data":[1,123],"mining":[2],"algorithms":[3,69],"do":[4],"not":[5,25],"make":[6],"use":[7],"of":[8,52,55,92],"existing":[9],"domain":[10],"knowledge":[11,42],"when":[12],"constructing":[13],"their":[14,32],"models.":[15,53],"This":[16,76],"can":[17,44],"lead":[18],"to":[19,31,39,48,81,88],"model":[20],"rejection":[21],"as":[22],"users":[23],"may":[24],"trust":[26],"models":[27],"that":[28,108,126],"behave":[29],"contrary":[30],"expectations.":[33],"Semantic":[34],"constraints":[35,60,111],"provide":[36],"a":[37,90,102],"way":[38],"encapsulate":[40],"this":[41],"which":[43],"then":[45],"be":[46],"used":[47],"guide":[49],"the":[50,56,62,98,113,127],"construction":[51],"One":[54],"most":[57],"studied":[58],"semantic":[59],"in":[61,86],"literature":[63],"is":[64],"monotonicity,":[65],"however":[66],"current":[67],"monotonically-aware":[68],"have":[70],"focused":[71],"on":[72],"ordinal":[73],"classification":[74],"problems.":[75],"paper":[77],"proposes":[78],"an":[79,82],"extension":[80],"ACO-based":[83],"regression":[84,94,104],"algorithm":[85,100,107,129],"order":[87],"extract":[89],"list":[91],"monotonic":[93,110,132],"rules.":[95],"We":[96],"compared":[97],"proposed":[99,128],"against":[101],"greedy":[103],"rule":[105],"induction":[106],"preserves":[109],"and":[112],"well-known":[114],"M5'":[115],"Rules.":[116],"Our":[117],"experiments":[118],"using":[119],"eight":[120],"publicly":[121],"available":[122],"sets":[124],"show":[125],"successfully":[130],"creates":[131],"rules":[133],"while":[134],"maintaining":[135],"predictive":[136],"accuracy.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-08-25T07:29:55.448023","created_date":"2025-10-10T00:00:00"}
