{"id":"https://openalex.org/W2955450195","doi":"https://doi.org/10.1109/snpd.2019.8935793","title":"Proposal of Home Context Recognition Method Using Feature Values of Cognitive API","display_name":"Proposal of Home Context Recognition Method Using Feature Values of Cognitive API","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2955450195","doi":"https://doi.org/10.1109/snpd.2019.8935793","mag":"2955450195"},"language":"en","primary_location":{"id":"doi:10.1109/snpd.2019.8935793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2019.8935793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","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/A5084127474","display_name":"Sinan Chen","orcid":"https://orcid.org/0000-0002-9898-7370"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Sinan Chen","raw_affiliation_strings":["Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada, Kobe, Japan","Kobe University, 1-1 Rokkodai-cho, Nada,Graduate School of System Informatics,Kobe,Japan,657-0011"],"affiliations":[{"raw_affiliation_string":"Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]},{"raw_affiliation_string":"Kobe University, 1-1 Rokkodai-cho, Nada,Graduate School of System Informatics,Kobe,Japan,657-0011","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103920360","display_name":"Sachio Saiki","orcid":"https://orcid.org/0009-0009-3556-6454"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sachio Saiki","raw_affiliation_strings":["Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada, Kobe, Japan","Kobe University, 1-1 Rokkodai-cho, Nada,Graduate School of System Informatics,Kobe,Japan,657-0011"],"affiliations":[{"raw_affiliation_string":"Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]},{"raw_affiliation_string":"Kobe University, 1-1 Rokkodai-cho, Nada,Graduate School of System Informatics,Kobe,Japan,657-0011","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076752003","display_name":"Masahide Nakamura","orcid":"https://orcid.org/0000-0002-1689-7620"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"education","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahide Nakamura","raw_affiliation_strings":["Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada, Kobe, Japan","Kobe University, 1-1 Rokkodai-cho, Nada,Graduate School of System Informatics,Kobe,Japan,657-0011"],"affiliations":[{"raw_affiliation_string":"Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]},{"raw_affiliation_string":"Kobe University, 1-1 Rokkodai-cho, Nada,Graduate School of System Informatics,Kobe,Japan,657-0011","institution_ids":["https://openalex.org/I65837984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084127474"],"corresponding_institution_ids":["https://openalex.org/I65837984"],"apc_list":null,"apc_paid":null,"fwci":0.1663,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46444888,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"68","issue":"511","first_page":"533","last_page":"538"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13382","display_name":"Robotics and Automated Systems","score":0.9632999897003174,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13382","display_name":"Robotics and Automated Systems","score":0.9632999897003174,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7494736313819885},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7053495645523071},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6784282922744751},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6033819317817688},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5801281332969666},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4986145496368408},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4629974961280823},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4110877811908722},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40002748370170593},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05962994694709778}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7494736313819885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7053495645523071},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6784282922744751},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6033819317817688},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5801281332969666},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4986145496368408},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4629974961280823},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4110877811908722},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40002748370170593},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05962994694709778},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/snpd.2019.8935793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snpd.2019.8935793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","raw_type":"proceedings-article"},{"id":"mag:2955450195","is_oa":false,"landing_page_url":"https://www.ieice.org/ken/paper/20190315J1K0/eng/","pdf_url":null,"source":{"id":"https://openalex.org/S4306512848","display_name":"IEICE Technical Report; IEICE Tech. Rep.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEICE Technical Report; IEICE Tech. Rep.","raw_type":null},{"id":"mag:3041309895","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002235000364260","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"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/W2594467375","https://openalex.org/W2919693742","https://openalex.org/W6981786155"],"related_works":["https://openalex.org/W2994823676","https://openalex.org/W2892259437","https://openalex.org/W2233838193","https://openalex.org/W169090763","https://openalex.org/W2050230532","https://openalex.org/W2889146846","https://openalex.org/W2898836677","https://openalex.org/W2586988759","https://openalex.org/W2949861479","https://openalex.org/W2956371155","https://openalex.org/W2003723718","https://openalex.org/W2026161366","https://openalex.org/W1980618358","https://openalex.org/W2138517257","https://openalex.org/W2672055271","https://openalex.org/W3172933942","https://openalex.org/W2053354347","https://openalex.org/W3099025572","https://openalex.org/W2347092114","https://openalex.org/W1499276978"],"abstract_inverted_index":{"The":[0,94],"emerging":[1],"deep":[2,21,76,156],"learning":[3,22,77],"technology":[4],"is":[5,59,88,99,108],"a":[6,55,70,79,118,174],"promising":[7],"means":[8],"for":[9,25,61,91,180],"context":[10,26,34,104,144,177],"recognition":[11,27,57,105,164,178],"with":[12,23,145,151,155,186],"multimedia":[13],"data.":[14],"We":[15],"are":[16,47,85],"interested":[17],"in":[18,28],"using":[19,136],"the":[20,32,36,39,42,75,113,128,131,137,143,152,158,166,176],"images":[24,84],"smart":[29],"homes.":[30],"In":[31,112],"home":[33],"recognition,":[35,125],"room":[37],"layout,":[38],"environment,":[40],"and":[41,126,169],"contexts":[43],"to":[44,52,100],"be":[45,184],"recognized":[46],"different":[48,63],"from":[49],"one":[50],"household":[51,182],"another.":[53],"Therefore,":[54],"unique":[56],"model":[58],"required":[60],"every":[62,181],"household.":[64],"For":[65],"this,":[66],"if":[67],"we":[68,116,141],"take":[69],"naive":[71],"approach":[72,154],"that":[73,107],"uses":[74,161],"directly,":[78],"huge":[80],"amount":[81],"of":[82,96,165],"labeled":[83],"required,":[86],"which":[87,121],"practically":[89],"impossible":[90],"general":[92,123],"households.":[93],"goal":[95],"this":[97],"research":[98],"develop":[101],"an":[102],"image-based":[103],"method":[106,160],"affordable":[109],"at":[110],"home.":[111],"proposed":[114,159],"method,":[115],"exploit":[117],"cognitive":[119,167],"API":[120],"performs":[122],"image":[124,132,163],"retrieve":[127],"information":[129],"within":[130],"as":[133,139],"text.":[134],"By":[135],"text":[138],"features,":[140],"classify":[142],"ordinal":[146],"supervised":[147],"machine":[148,171],"learning.":[149,172],"Compared":[150],"expensive":[153],"learning,":[157],"generic":[162],"API,":[168],"light-weight":[170],"As":[173],"result,":[175],"customized":[179],"can":[183],"achieved":[185],"much":[187],"less":[188],"effort.":[189]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}