{"id":"https://openalex.org/W3044929070","doi":null,"title":"Towards Knowledge Infusion for Robust and Transferable Machine Learning in IoT","display_name":"Towards Knowledge Infusion for Robust and Transferable Machine Learning in IoT","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3044929070","mag":"3044929070"},"language":"en","primary_location":{"id":"pmh:oai:ronpub.com:OJIOT_2020v6i1n04_Fuerst","doi":null,"is_oa":true,"landing_page_url":"https://www.ronpub.com/ojiot/ojiot_2020v6i1n04_fuerst.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400266","display_name":"RonPub -- Research Online Publishing (RonPub UG)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Jonathan F\u00fcrst, Mauricio Fadel Argerich, Bin Cheng and Ern\u00f6 Kovacs: Towards Knowledge Infusion for Robust and Transferable Machine Learning in IoT, Open Journal of Internet Of Things (OJIOT), 6 (1), pages 24-34, 2020","raw_type":"info:eu-repo/semantics/article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ronpub.com/ojiot/ojiot_2020v6i1n04_fuerst.html","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010965443","display_name":"Jonathan F\u00fcrst","orcid":"https://orcid.org/0000-0002-4062-1827","observed_orcids":["https://orcid.org/0000-0002-4062-1827"]},"institutions":[{"id":"https://openalex.org/I83467386","display_name":"IT University of Copenhagen","ror":"https://ror.org/02309jg23","country_code":"DK","type":"education","lineage":["https://openalex.org/I83467386"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Jonathan F\u00fcrst","raw_affiliation_strings":["IT University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-4062-1827","affiliations":[{"raw_affiliation_string":"IT University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I83467386"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053272278","display_name":"Mauricio Fadel Argerich","orcid":"https://orcid.org/0009-0008-9348-8426","observed_orcids":["https://orcid.org/0009-0008-9348-8426"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mauricio Fadel Argerich","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0008-9348-8426","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101919963","display_name":"Bin Cheng","orcid":"https://orcid.org/0000-0002-7907-9852","observed_orcids":["https://orcid.org/0000-0002-7907-9852"]},"institutions":[{"id":"https://openalex.org/I149899117","display_name":"Max Planck Society","ror":"https://ror.org/01hhn8329","country_code":"DE","type":"nonprofit","lineage":["https://openalex.org/I149899117"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bin Cheng","raw_affiliation_strings":["Max Planck Society, Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0002-7907-9852","affiliations":[{"raw_affiliation_string":"Max Planck Society, Munich, Germany","institution_ids":["https://openalex.org/I149899117"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001582325","display_name":"Ern\u0151 Kov\u00e1cs","orcid":"https://orcid.org/0000-0002-4010-5208","observed_orcids":["https://orcid.org/0000-0002-4010-5208"]},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ern\u0151 Kov\u00e1cs","raw_affiliation_strings":["NEC (Japan), Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-4010-5208","affiliations":[{"raw_affiliation_string":"NEC (Japan), Tokyo, Japan","institution_ids":["https://openalex.org/I118347220"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5856,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.69127967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":"6","issue":"1","first_page":"24","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.4772999882698059,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.4772999882698059,"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/T13038","display_name":"Internet of Things and AI","score":0.24940000474452972,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.09380000084638596,"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/knowledge-injection","display_name":"knowledge injection","score":0.9269999861717224},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.953000009059906},{"id":"https://openalex.org/keywords/weakly-supervised-learning","display_name":"weakly supervised learning","score":0.781000018119812},{"id":"https://openalex.org/keywords/label-generation","display_name":"label generation","score":0.5329999923706055},{"id":"https://openalex.org/keywords/labeling-functions","display_name":"labeling functions","score":0.6990000009536743},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"domain knowledge","score":0.6669999957084656},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"knowledge base","score":0.8159999847412109},{"id":"https://openalex.org/keywords/domain-expert-knowledge","display_name":"domain expert knowledge","score":0.6830000281333923},{"id":"https://openalex.org/keywords/transferable-machine-learning","display_name":"transferable machine learning","score":0.8379999995231628},{"id":"https://openalex.org/keywords/robust-machine-learning","display_name":"robust machine learning","score":0.625}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.808384895324707},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8037552237510681},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6773008108139038},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6511508226394653},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6488586664199829},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.5725024342536926},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5098875761032104},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.47331488132476807},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4702621400356293},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:ronpub.com:OJIOT_2020v6i1n04_Fuerst","doi":null,"is_oa":true,"landing_page_url":"https://www.ronpub.com/ojiot/ojiot_2020v6i1n04_fuerst.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400266","display_name":"RonPub -- Research Online Publishing (RonPub UG)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Jonathan F\u00fcrst, Mauricio Fadel Argerich, Bin Cheng and Ern\u00f6 Kovacs: Towards Knowledge Infusion for Robust and Transferable Machine Learning in IoT, Open Journal of Internet Of Things (OJIOT), 6 (1), pages 24-34, 2020","raw_type":"info:eu-repo/semantics/article"},{"id":"mag:3044929070","doi":null,"is_oa":false,"landing_page_url":"http://www.ronpub.com/OJIOT_2020v6i1n04_Fuerst.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306421051","display_name":"The Internet of Things","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"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":false,"raw_source_name":"The Internet of Things","raw_type":null}],"best_oa_location":{"id":"pmh:oai:ronpub.com:OJIOT_2020v6i1n04_Fuerst","doi":null,"is_oa":true,"landing_page_url":"https://www.ronpub.com/ojiot/ojiot_2020v6i1n04_fuerst.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400266","display_name":"RonPub -- Research Online Publishing (RonPub UG)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Jonathan F\u00fcrst, Mauricio Fadel Argerich, Bin Cheng and Ern\u00f6 Kovacs: Towards Knowledge Infusion for Robust and Transferable Machine Learning in IoT, Open Journal of Internet Of Things (OJIOT), 6 (1), pages 24-34, 2020","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"score":0.7207000255584717,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1989750313","https://openalex.org/W2076063813","https://openalex.org/W2108328714","https://openalex.org/W2108467170","https://openalex.org/W2136317921","https://openalex.org/W2145339207","https://openalex.org/W2148143831","https://openalex.org/W2165698076","https://openalex.org/W2397581010","https://openalex.org/W2604259521","https://openalex.org/W2746791238","https://openalex.org/W2769041395","https://openalex.org/W2810602713","https://openalex.org/W2884890129","https://openalex.org/W2887024656","https://openalex.org/W2888562230","https://openalex.org/W2898045695","https://openalex.org/W2903440991","https://openalex.org/W2962825873","https://openalex.org/W2963575966","https://openalex.org/W2979765357"],"related_works":["https://openalex.org/W2773977228","https://openalex.org/W4389443059","https://openalex.org/W2072238055","https://openalex.org/W3107900872","https://openalex.org/W2784459116","https://openalex.org/W4406460155","https://openalex.org/W3164323003","https://openalex.org/W3177318704","https://openalex.org/W6922765251","https://openalex.org/W6903713108"],"abstract_inverted_index":{"Machine":[0],"learning":[1,87,126,209,270],"(ML)":[2],"applications":[3],"in":[4,37,46,76,91,116,127,154,217],"Internet":[5],"of":[6,54,168,220,242,254],"Things":[7],"(IoT)":[8],"scenarios":[9,129],"face":[10],"the":[11,43,47,52,132,140,198,218,232,252,278],"issue":[12],"that":[13,104,182],"supervision":[14,133],"signals,":[15],"such":[16],"as":[17],"labeled":[18],"data,":[19],"are":[20],"scarce":[21],"and":[22,67,84,201,260],"expensive":[23],"to":[24,33,81,130,143,192,196,238,250,263],"obtain.":[25],"For":[26],"example,":[27],"it":[28,79,265],"often":[29],"requires":[30],"a":[31,38,60,136,165,178],"human":[32],"manually":[34],"label":[35],"events":[36,45],"data":[39,69],"stream":[40],"by":[41],"observing":[42],"same":[44],"real":[48],"world.":[49],"In":[50,93,203,245],"addition,":[51],"performance":[53],"trained":[55],"models":[56],"usually":[57],"depends":[58],"on":[59,147,175,184],"specific":[61],"context:":[62],"(1)":[63,135],"location,":[64],"(2)":[65,187],"time":[66],"(3)":[68],"quality.":[70],"This":[71],"context":[72],"is":[73],"not":[74],"static":[75],"reality,":[77],"making":[78],"hard":[80],"achieve":[82],"robust":[83],"transferable":[85],"machine":[86,125,269],"for":[88,139,160],"IoT":[89,128,141],"systems":[90],"practice.":[92],"this":[94],"paper,":[95],"we":[96,105,110,118,248],"address":[97],"these":[98,236],"challenges":[99],"with":[100,122,170,177,226,266],"an":[101,224],"envisioned":[102],"method":[103],"name":[106],"Knowledge":[107],"Infusion.":[108],"First,":[109],"present":[111],"two":[112],"past":[113],"case":[114],"studies":[115],"which":[117],"combined":[119],"external":[120,148,228],"knowledge":[121,149,243,246,255,258],"traditional":[123,267],"data-driven":[124,268],"ease":[131],"effort:":[134],"weak-supervision":[137],"approach":[138],"domain":[142,151,261],"auto-generate":[144],"labels":[145],"based":[146],"(e.g.,":[150],"knowledge)":[152],"encoded":[153],"simple":[155],"labeling":[156,173],"functions.":[157],"Our":[158],"evaluation":[159],"transport":[161],"mode":[162],"classification":[163],"achieves":[164,210],"micro-F1":[166],"score":[167],"80.2%,":[169],"only":[171],"seven":[172],"functions,":[174],"par":[176],"fully":[179],"supervised":[180],"model":[181],"relies":[183],"hand-labeled":[185],"data.":[186],"We":[188,230],"introduce":[189],"guiding":[190],"functions":[191],"Reinforcement":[193],"Learning":[194],"(RL)":[195],"guide":[197],"agents'":[199],"decisions":[200],"experience.":[202],"initial":[204],"experiments,":[205],"our":[206,240],"guided":[207],"reinforcement":[208],"more":[211],"than":[212,223],"three":[213],"times":[214],"higher":[215],"reward":[216],"beginning":[219],"its":[221],"training":[222],"agent":[225],"no":[227],"knowledge.":[229],"use":[231],"lessons":[233],"learned":[234],"from":[235,256],"experiences":[237],"develop":[239],"vision":[241],"infusion.":[244],"infusion,":[247],"aim":[249],"automate":[251],"inclusion":[253],"existing":[257],"bases":[259],"experts":[262],"combine":[264],"techniques":[271],"during":[272,277],"setup/training":[273],"phase,":[274],"but":[275],"also":[276],"execution":[279],"phase.":[280]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2020-07-29T00:00:00"}