{"id":"https://openalex.org/W2590299625","doi":"https://doi.org/10.1109/icci-cc.2016.7862039","title":"Extracting time-oriented relationships of nutrients to losing body fat mass using inductive logic programming","display_name":"Extracting time-oriented relationships of nutrients to losing body fat mass using inductive logic programming","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2590299625","doi":"https://doi.org/10.1109/icci-cc.2016.7862039","mag":"2590299625"},"language":"en","primary_location":{"id":"doi:10.1109/icci-cc.2016.7862039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2016.7862039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","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/A5058119886","display_name":"Sho Ushikubo","orcid":null},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Sho Ushikubo","raw_affiliation_strings":["Faculty of Sci. and Tech., Tokyo University of Science, Noda-shi, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Sci. and Tech., Tokyo University of Science, Noda-shi, Japan","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022566633","display_name":"Katsutoshi Kanamori","orcid":null},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Katsutoshi Kanamori","raw_affiliation_strings":["Faculty of Sci. and Tech., Tokyo University of Science, Noda-shi, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Sci. and Tech., Tokyo University of Science, Noda-shi, Japan","institution_ids":["https://openalex.org/I161296585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004082634","display_name":"Hayato Ohwada","orcid":"https://orcid.org/0000-0001-5621-6984"},"institutions":[{"id":"https://openalex.org/I161296585","display_name":"Tokyo University of Science","ror":"https://ror.org/05sj3n476","country_code":"JP","type":"education","lineage":["https://openalex.org/I161296585"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hayato Ohwada","raw_affiliation_strings":["Faculty of Sci. and Tech., Tokyo University of Science, Noda-shi, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Sci. and Tech., Tokyo University of Science, Noda-shi, Japan","institution_ids":["https://openalex.org/I161296585"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5058119886"],"corresponding_institution_ids":["https://openalex.org/I161296585"],"apc_list":null,"apc_paid":null,"fwci":0.4285,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.8088783,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"226","last_page":"230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9656000137329102,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9656000137329102,"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/T11727","display_name":"Advanced Algebra and Logic","score":0.9524000287055969,"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"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9523000121116638,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/pantothenic-acid","display_name":"Pantothenic acid","score":0.6201843023300171},{"id":"https://openalex.org/keywords/nutrient","display_name":"Nutrient","score":0.6031913161277771},{"id":"https://openalex.org/keywords/fat-mass","display_name":"Fat mass","score":0.5490350127220154},{"id":"https://openalex.org/keywords/vitamin","display_name":"Vitamin","score":0.4948248267173767},{"id":"https://openalex.org/keywords/inductive-logic-programming","display_name":"Inductive logic programming","score":0.46546176075935364},{"id":"https://openalex.org/keywords/fat-soluble-vitamin","display_name":"Fat-Soluble Vitamin","score":0.45165881514549255},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42311325669288635},{"id":"https://openalex.org/keywords/obesity","display_name":"Obesity","score":0.294333815574646},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2802659869194031},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2741760015487671},{"id":"https://openalex.org/keywords/endocrinology","display_name":"Endocrinology","score":0.2360578179359436},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.23422405123710632}],"concepts":[{"id":"https://openalex.org/C2780420027","wikidata":"https://www.wikidata.org/wiki/Q179894","display_name":"Pantothenic acid","level":3,"score":0.6201843023300171},{"id":"https://openalex.org/C142796444","wikidata":"https://www.wikidata.org/wiki/Q181394","display_name":"Nutrient","level":2,"score":0.6031913161277771},{"id":"https://openalex.org/C2993503589","wikidata":"https://www.wikidata.org/wiki/Q193583","display_name":"Fat mass","level":3,"score":0.5490350127220154},{"id":"https://openalex.org/C2776940978","wikidata":"https://www.wikidata.org/wiki/Q34956","display_name":"Vitamin","level":2,"score":0.4948248267173767},{"id":"https://openalex.org/C2779382394","wikidata":"https://www.wikidata.org/wiki/Q1464197","display_name":"Inductive logic programming","level":2,"score":0.46546176075935364},{"id":"https://openalex.org/C2909598748","wikidata":"https://www.wikidata.org/wiki/Q34956","display_name":"Fat-Soluble Vitamin","level":3,"score":0.45165881514549255},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42311325669288635},{"id":"https://openalex.org/C511355011","wikidata":"https://www.wikidata.org/wiki/Q12174","display_name":"Obesity","level":2,"score":0.294333815574646},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2802659869194031},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2741760015487671},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.2360578179359436},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.23422405123710632},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icci-cc.2016.7862039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2016.7862039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W134039131","https://openalex.org/W277549847","https://openalex.org/W1471691751","https://openalex.org/W1535300873","https://openalex.org/W1872037639","https://openalex.org/W1932116449","https://openalex.org/W1934358478","https://openalex.org/W1966254134","https://openalex.org/W1973157975","https://openalex.org/W1974831129","https://openalex.org/W1979588981","https://openalex.org/W2008533266","https://openalex.org/W2039469542","https://openalex.org/W2087347434","https://openalex.org/W2127877778","https://openalex.org/W2133148459","https://openalex.org/W2159038248","https://openalex.org/W2218089048","https://openalex.org/W2520858206","https://openalex.org/W2574352594","https://openalex.org/W2911964244","https://openalex.org/W3202522595","https://openalex.org/W4235942377","https://openalex.org/W4236137412"],"related_works":["https://openalex.org/W2440951634","https://openalex.org/W2331417415","https://openalex.org/W2081640838","https://openalex.org/W2406156554","https://openalex.org/W4225693071","https://openalex.org/W2569727378","https://openalex.org/W125112755","https://openalex.org/W2320359821","https://openalex.org/W2418808159","https://openalex.org/W2413409987"],"abstract_inverted_index":{"This":[0],"study":[1],"was":[2,149],"performed":[3],"to":[4,14,34,95,117,130,162],"extract":[5],"rules":[6,39,105,124],"for":[7,40],"reducing":[8,41,152],"body":[9,42,71,132,153,164],"fat":[10,30,43,72,133,154,165],"mass":[11,31,44,73,134,166],"so":[12],"as":[13,83],"prevent":[15],"lifestyle-related":[16,35],"diseases.":[17,36],"Lifestyle-related":[18],"diseases":[19],"have":[20],"been":[21],"increasing":[22],"in":[23,59,151],"Japan,":[24],"even":[25],"among":[26],"younger":[27],"people.":[28],"Body":[29],"is":[32,45],"related":[33,161],"Hence,":[37],"finding":[38],"very":[46],"meaningful.":[47],"We":[48,89],"obtained":[49],"lifestyle":[50],"time-series":[51],"data":[52,66,98,116],"on":[53,136],"five":[54],"male":[55],"subjects":[56],"who":[57],"are":[58],"their":[60],"20s":[61],"and":[62,77,86,145,175],"not":[63],"obese.":[64],"The":[65],"includes":[67],"the":[68,115],"amount":[69],"of":[70,74,80,113,125,128,140],"each":[75],"subject":[76],"a":[78,111],"variety":[79],"features":[81],"such":[82],"sleep,":[84],"exercise,":[85],"nutrient":[87],"intake.":[88],"used":[90],"Inductive":[91],"Logic":[92],"Programming":[93],"(ILP)":[94],"apply":[96],"this":[97],"because":[99],"ILP":[100,120],"can":[101],"more":[102],"flexibly":[103],"learn":[104],"than":[106],"other":[107],"machine-learning":[108],"methods.":[109],"As":[110],"result":[112],"applying":[114],"ILP,":[118],"our":[119],"system":[121],"successfully":[122],"extracted":[123],"time-oriented":[126],"relationships":[127],"nutrients":[129,142,160],"decrease":[131],"based":[135],"limited":[137],"data.":[138],"Intake":[139],"various":[141],"one":[143],"day":[144],"two":[146],"days":[147],"prior":[148],"effective":[150],"mass.":[155],"Moreover,":[156],"we":[157],"determined":[158],"that":[159],"losing":[163],"include":[167],"vitamin":[168,173],"B2,":[169],"pantothenic":[170],"acid,":[171],"fat,":[172],"B1,":[174],"biotin.":[176]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}