{"id":"https://openalex.org/W7138867466","doi":"https://doi.org/10.1109/kst67832.2026.11431865","title":"Daily Life Pattern Extraction in Single Person Households","display_name":"Daily Life Pattern Extraction in Single Person Households","publication_year":2026,"publication_date":"2026-01-21","ids":{"openalex":"https://openalex.org/W7138867466","doi":"https://doi.org/10.1109/kst67832.2026.11431865"},"language":null,"primary_location":{"id":"doi:10.1109/kst67832.2026.11431865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kst67832.2026.11431865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 18th International Conference on Knowledge and Smart Technology (KST)","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/A5107879877","display_name":"K. Lee","orcid":"https://orcid.org/0000-0002-3680-7039"},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyungsuk Lee","raw_affiliation_strings":["Dongguk University,Department of Computer Engineering and AI,Seoul,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dongguk University,Department of Computer Engineering and AI,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I205490536"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008004104","display_name":"In-Nea Wang","orcid":"https://orcid.org/0000-0002-5427-9129"},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"In-Nea Wang","raw_affiliation_strings":["IoT Convergence and Open Sharing System Dongguk University,Seoul,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IoT Convergence and Open Sharing System Dongguk University,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I205490536"]}]},{"author_position":"last","author":{"id":null,"display_name":"Junho Jeong","orcid":null},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junho Jeong","raw_affiliation_strings":["Dongguk University,Department of Computer Engineering and AI,Seoul,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dongguk University,Department of Computer Engineering and AI,Seoul,Republic of Korea","institution_ids":["https://openalex.org/I205490536"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205490536"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.314383,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"350","last_page":"355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.5515999794006348,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.5515999794006348,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.14329999685287476,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.05739999935030937,"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/cluster-analysis","display_name":"Cluster analysis","score":0.5990999937057495},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5878000259399414},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5800999999046326},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5726000070571899},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5044999718666077},{"id":"https://openalex.org/keywords/data-extraction","display_name":"Data extraction","score":0.38760000467300415},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.33379998803138733}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5990999937057495},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5878000259399414},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5800999999046326},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5726000070571899},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5088000297546387},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5044999718666077},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5011000037193298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46619999408721924},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.38760000467300415},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.3310000002384186},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3303999900817871},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3059000074863434},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2858000099658966},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C293773","wikidata":"https://www.wikidata.org/wiki/Q7608015","display_name":"Step detection","level":3,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/kst67832.2026.11431865","is_oa":false,"landing_page_url":"https://doi.org/10.1109/kst67832.2026.11431865","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 18th International Conference on Knowledge and Smart Technology (KST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4617359641","display_name":null,"funder_award_id":"2023-0-00049","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"research":[1,41],"utilizing":[2],"smart":[3],"home":[4],"technology":[5],"for":[6,72],"anomaly":[7,73],"detection":[8,74],"in":[9,47],"single-person":[10],"households":[11],"has":[12],"been":[13],"actively":[14],"conducted.":[15],"However,":[16],"real-world":[17],"sensor":[18],"data":[19,100,161],"flaws,":[20],"such":[21,53,110],"as":[22,54,56,106,111,163,170],"noise":[23],"and":[24,68,95,97,114,128,156],"battery":[25],"discharge,":[26],"cause":[27],"the":[28,70,141,145,176],"'Garbage":[29],"In,":[30],"Garbage":[31],"Out":[32],"(GIGO)'":[33],"problem,":[34],"thereby":[35,174],"undermining":[36],"model":[37],"reliability.":[38],"Furthermore,":[39],"existing":[40],"on":[42,60,76],"fixed":[43],"sensors":[44,90],"faces":[45],"limitations":[46],"logically":[48],"explaining":[49],"complex":[50],"life":[51,78,108,181],"patterns,":[52,79],"'sleep',":[55],"it":[57],"relies":[58],"solely":[59],"simple":[61],"activation":[62],"status.":[63],"To":[64],"address":[65],"these":[66,119],"issues":[67],"lay":[69],"foundation":[71],"based":[75],"daily":[77,107,180],"this":[80],"study":[81],"proposes":[82],"a":[83],"robust":[84,179],"extraction":[85,177],"methodology":[86],"that":[87,140],"fuses":[88],"heterogeneous":[89],"including":[91],"respiration,":[92],"heart":[93],"rate":[94],"illuminance":[96],"transforms":[98],"raw":[99],"into":[101],"'Interpretable":[102],"Representations',":[103],"referred":[104],"to":[105],"patterns":[109,120],"sleep,":[112],"outing,":[113],"activity.":[115],"Specifically,":[116],"we":[117],"construct":[118],"by":[121,148],"determining":[122],"dynamic":[123],"thresholds":[124],"via":[125],"K-Means":[126],"clustering":[127],"comprehensively":[129],"considering":[130],"global":[131],"configuration":[132],"of":[133,178],"all":[134],"sensors.":[135],"Case":[136],"Study":[137],"results":[138],"demonstrate":[139],"proposed":[142],"method":[143],"resolves":[144],"GIGO":[146],"problem":[147],"clearly":[149],"distinguishing":[150],"'long-term":[151],"absences'":[152],"from":[153,167],"'long":[154],"sleep'":[155],"accurately":[157],"differentiating":[158],"actual":[159],"missing":[160],"marked":[162],"'":[164,166,171],"NaN":[165],"non-occurrences":[168],"represented":[169],"0":[172],"',":[173],"enabling":[175],"patterns.":[182]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2026-03-20T00:00:00"}