{"id":"https://openalex.org/W2957294211","doi":"https://doi.org/10.1145/3319619.3326784","title":"Predictive model for epistasis-based basis evaluation on pseudo-boolean function using deep neural networks","display_name":"Predictive model for epistasis-based basis evaluation on pseudo-boolean function using deep neural networks","publication_year":2019,"publication_date":"2019-07-10","ids":{"openalex":"https://openalex.org/W2957294211","doi":"https://doi.org/10.1145/3319619.3326784","mag":"2957294211"},"language":"en","primary_location":{"id":"doi:10.1145/3319619.3326784","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3319619.3326784","pdf_url":null,"source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","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/A5101404636","display_name":"Yonghoon Kim","orcid":"https://orcid.org/0000-0001-6022-4354"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yong-Hoon Kim","raw_affiliation_strings":["Kwangwoon Univ., Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Kwangwoon Univ., Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100446510","display_name":"Junghwan Lee","orcid":"https://orcid.org/0000-0002-7447-6656"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junghwan Lee","raw_affiliation_strings":["Kwangwoon Univ., Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Kwangwoon Univ., Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046031351","display_name":"Yong-Hyuk Kim","orcid":"https://orcid.org/0000-0002-0492-0889"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yong-Hyuk Kim","raw_affiliation_strings":["Kwangwoon Univ., Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Kwangwoon Univ., Seoul, Republic of Korea","institution_ids":["https://openalex.org/I161024014"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101404636"],"corresponding_institution_ids":["https://openalex.org/I161024014"],"apc_list":null,"apc_paid":null,"fwci":0.2624,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59520137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"61","last_page":"62"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9769999980926514,"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/T10320","display_name":"Neural Networks and Applications","score":0.9769999980926514,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9620000123977661,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9480000138282776,"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/basis","display_name":"Basis (linear algebra)","score":0.6407952308654785},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6175644397735596},{"id":"https://openalex.org/keywords/boolean-function","display_name":"Boolean function","score":0.6139476895332336},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5863738656044006},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4958561360836029},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4956551790237427},{"id":"https://openalex.org/keywords/basis-function","display_name":"Basis function","score":0.4628196656703949},{"id":"https://openalex.org/keywords/boolean-network","display_name":"Boolean network","score":0.45945435762405396},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38665398955345154},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3095688819885254},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2482292354106903},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.07456231117248535}],"concepts":[{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.6407952308654785},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6175644397735596},{"id":"https://openalex.org/C187455244","wikidata":"https://www.wikidata.org/wiki/Q942353","display_name":"Boolean function","level":2,"score":0.6139476895332336},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5863738656044006},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4958561360836029},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4956551790237427},{"id":"https://openalex.org/C5917680","wikidata":"https://www.wikidata.org/wiki/Q2621825","display_name":"Basis function","level":2,"score":0.4628196656703949},{"id":"https://openalex.org/C134444547","wikidata":"https://www.wikidata.org/wiki/Q585230","display_name":"Boolean network","level":3,"score":0.45945435762405396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38665398955345154},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3095688819885254},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2482292354106903},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.07456231117248535},{"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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3319619.3326784","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3319619.3326784","pdf_url":null,"source":{"id":"https://openalex.org/S4363608771","display_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W19571631","https://openalex.org/W2874710892","https://openalex.org/W2888618521"],"related_works":["https://openalex.org/W2006953814","https://openalex.org/W2542637001","https://openalex.org/W1972782945","https://openalex.org/W3212981098","https://openalex.org/W4221090543","https://openalex.org/W2130622405","https://openalex.org/W2109887391","https://openalex.org/W1748978355","https://openalex.org/W1819996744","https://openalex.org/W2154858558"],"abstract_inverted_index":{"Complexity":[0],"of":[1,24,26,89],"a":[2,33,40,61,67,72],"problem":[3,49],"can":[4],"be":[5],"substantially":[6],"reduced":[7],"through":[8],"basis":[9,20,27,41,53,68,80],"change,":[10],"however,":[11],"it":[12],"is":[13,55,63],"not":[14],"easy":[15],"to":[16,38,65],"find":[17],"an":[18],"appropriate":[19],"in":[21],"representation":[22],"because":[23],"difficulty":[25],"evaluation.":[28],"To":[29],"address":[30],"this":[31,59],"issue,":[32],"method":[34,62],"has":[35,96],"been":[36,97],"proposed":[37,64,103],"evaluate":[39,66],"based":[42],"on":[43],"the":[44,48,52,76,79,94,102],"epistasis":[45,77,95],"that":[46,74],"shows":[47],"difficulty.":[50],"However,":[51],"evaluation":[54],"very":[56],"time-consuming.":[57],"In":[58],"study,":[60],"quickly":[69],"by":[70,81,100],"developing":[71],"model":[73],"estimates":[75],"from":[78],"using":[82,101],"deep":[83],"neural":[84],"networks.":[85],"As":[86],"experimental":[87],"results":[88],"variant-onemax":[90],"and":[91],"NK-landscape":[92],"problems,":[93],"estimated":[98],"successfully":[99],"method.":[104]},"counts_by_year":[{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
