{"id":"https://openalex.org/W2904798028","doi":"https://doi.org/10.1609/aaai.v33i01.33017699","title":"Distribution-Based Semi-Supervised Learning for Activity Recognition","display_name":"Distribution-Based Semi-Supervised Learning for Activity Recognition","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2904798028","doi":"https://doi.org/10.1609/aaai.v33i01.33017699","mag":"2904798028"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33017699","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017699","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4765/4643","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4765/4643","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052221167","display_name":"Hangwei Qian","orcid":"https://orcid.org/0000-0003-4831-0748"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Hangwei Qian","raw_affiliation_strings":["Nanyang Technological University"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082984558","display_name":"Sinno Jialin Pan","orcid":"https://orcid.org/0000-0001-6565-3836"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Sinno Jialin Pan","raw_affiliation_strings":["Nanyang Technological University"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100382077","display_name":"Chunyan Miao","orcid":"https://orcid.org/0000-0002-0300-3448"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chunyan Miao","raw_affiliation_strings":["Nanyang Technological University"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5052221167"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.9792,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.81520223,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"33","issue":"01","first_page":"7699","last_page":"7706"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998999834060669,"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":0.9998999834060669,"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":0.996999979019165,"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":0.9940000176429749,"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/reproducing-kernel-hilbert-space","display_name":"Reproducing kernel Hilbert space","score":0.7621309757232666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6798408031463623},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6725654602050781},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6417818069458008},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5979348421096802},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5573827624320984},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5228786468505859},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5187283158302307},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5112545490264893},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5057976245880127},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.492390513420105},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.474290668964386},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.4276670217514038},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.417038232088089},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4140605628490448},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.2975636124610901},{"id":"https://openalex.org/keywords/hilbert-space","display_name":"Hilbert space","score":0.18873977661132812},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18594849109649658}],"concepts":[{"id":"https://openalex.org/C80884492","wikidata":"https://www.wikidata.org/wiki/Q3345678","display_name":"Reproducing kernel Hilbert space","level":3,"score":0.7621309757232666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6798408031463623},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6725654602050781},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6417818069458008},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5979348421096802},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5573827624320984},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5228786468505859},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5187283158302307},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5112545490264893},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5057976245880127},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.492390513420105},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.474290668964386},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.4276670217514038},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.417038232088089},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4140605628490448},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.2975636124610901},{"id":"https://openalex.org/C62799726","wikidata":"https://www.wikidata.org/wiki/Q190056","display_name":"Hilbert space","level":2,"score":0.18873977661132812},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18594849109649658},{"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/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v33i01.33017699","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017699","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4765/4643","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/106004","is_oa":false,"landing_page_url":"http://hdl.handle.net/10220/49629","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33017699","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33017699","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4765/4643","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8100000023841858,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2904798028.pdf","grobid_xml":"https://content.openalex.org/works/W2904798028.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W22482183","https://openalex.org/W92894758","https://openalex.org/W1565176583","https://openalex.org/W1572369853","https://openalex.org/W1991468035","https://openalex.org/W2017634428","https://openalex.org/W2023302299","https://openalex.org/W2054780155","https://openalex.org/W2104290444","https://openalex.org/W2105608756","https://openalex.org/W2108307068","https://openalex.org/W2114506737","https://openalex.org/W2119393863","https://openalex.org/W2124823771","https://openalex.org/W2136010533","https://openalex.org/W2136440798","https://openalex.org/W2136504847","https://openalex.org/W2144902422","https://openalex.org/W2148029428","https://openalex.org/W2153635508","https://openalex.org/W2158690549","https://openalex.org/W2164274563","https://openalex.org/W2171837816","https://openalex.org/W2247607085","https://openalex.org/W2273937221","https://openalex.org/W2418306335","https://openalex.org/W2516027932","https://openalex.org/W2540822603","https://openalex.org/W2593796416","https://openalex.org/W2789084131","https://openalex.org/W2920725015","https://openalex.org/W2952400611","https://openalex.org/W2997701990","https://openalex.org/W3101183984","https://openalex.org/W3120421331","https://openalex.org/W4297068198","https://openalex.org/W6628746421","https://openalex.org/W6675972678","https://openalex.org/W6677803693","https://openalex.org/W6680140577","https://openalex.org/W6681302627","https://openalex.org/W7048487627"],"related_works":["https://openalex.org/W2110459882","https://openalex.org/W4294974824","https://openalex.org/W2538661024","https://openalex.org/W3077461311","https://openalex.org/W2108806452","https://openalex.org/W2604407846","https://openalex.org/W2368752996","https://openalex.org/W2160952319","https://openalex.org/W2156671090","https://openalex.org/W98693656"],"abstract_inverted_index":{"Supervised":[0],"learning":[1,45],"methods":[2,56,63],"have":[3,50],"been":[4],"widely":[5],"applied":[6],"to":[7,33,41,53,90,192],"activity":[8],"recognition.":[9],"The":[10,29,95,156],"prevalent":[11],"success":[12],"of":[13,100,124,167,196],"existing":[14,55,60],"methods,":[15],"however,":[16],"has":[17],"two":[18,48],"crucial":[19,40],"prerequisites:":[20],"proper":[21],"feature":[22,61],"extraction":[23,62],"and":[24,134,141],"sufficient":[25],"labeled":[26,70,140,182],"training":[27,137],"data.":[28],"former":[30],"is":[31,39,98,158,178],"important":[32],"differentiate":[34],"activities,":[35],"while":[36,69],"the":[37,92,112,151,163,168,173,181,194],"latter":[38],"build":[42],"a":[43,83,129,132,144,176],"precise":[44],"model.":[46],"These":[47],"prerequisites":[49],"become":[51],"bottlenecks":[52],"make":[54],"more":[57],"practical.":[58],"Most":[59],"highly":[64],"depend":[65],"on":[66,188],"domain":[67,107],"knowledge,":[68],"data":[71,122],"requires":[72],"intensive":[73],"human":[74],"annotation":[75,114],"effort.":[76],"Therefore,":[77],"in":[78,128,172],"this":[79],"paper,":[80],"we":[81,120],"propose":[82],"novel":[84],"method,":[85],"named":[86],"Distribution-based":[87],"Semi-Supervised":[88],"Learning,":[89],"tackle":[91],"aforementioned":[93],"limitations.":[94],"proposed":[96],"method":[97,198],"capable":[99],"automatically":[101],"extracting":[102],"powerful":[103],"features":[104],"with":[105,180,200],"no":[106],"knowledge":[108],"required,":[109],"meanwhile,":[110],"alleviating":[111],"heavy":[113],"effort":[115],"through":[116],"semi-supervised":[117],"learning.":[118],"Specifically,":[119],"treat":[121],"stream":[123],"sensor":[125],"readings":[126],"received":[127],"period":[130],"as":[131],"distribution,":[133],"map":[135],"all":[136],"distributions,":[138],"including":[139],"unlabeled,":[142],"into":[143],"reproducing":[145],"kernel":[146,152],"Hilbert":[147],"space":[148],"(RKHS)":[149],"using":[150],"mean":[153],"embedding":[154],"technique.":[155],"RKHS":[157],"further":[159],"altered":[160,174],"by":[161],"exploiting":[162],"underlying":[164],"geometry":[165],"structure":[166],"unlabeled":[169],"distributions.":[170,183],"Finally,":[171],"RKHS,":[175],"classifier":[177],"trained":[179],"We":[184],"conduct":[185],"extensive":[186],"experiments":[187],"three":[189],"public":[190],"datasets":[191],"verify":[193],"effectiveness":[195],"our":[197],"compared":[199],"state-of-the-art":[201],"baselines.":[202]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}