{"id":"https://openalex.org/W2766321935","doi":"https://doi.org/10.23919/eusipco.2017.8081216","title":"Active learning with cross-dataset validation in event-based non-intrusive load monitoring","display_name":"Active learning with cross-dataset validation in event-based non-intrusive load monitoring","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2766321935","doi":"https://doi.org/10.23919/eusipco.2017.8081216","mag":"2766321935"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2017.8081216","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","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/A5068028263","display_name":"Florian Liebgott","orcid":"https://orcid.org/0000-0002-7941-100X"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]},{"id":"https://openalex.org/I4210121626","display_name":"Signal Processing (United States)","ror":"https://ror.org/021gzyw51","country_code":"US","type":"company","lineage":["https://openalex.org/I4210121626"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"Florian Liebgott","raw_affiliation_strings":["Institute of Signal Processing and System Theory, University of Stuttgart"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Signal Processing and System Theory, University of Stuttgart","institution_ids":["https://openalex.org/I100066346","https://openalex.org/I4210121626"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101717968","display_name":"Bin Yang","orcid":"https://orcid.org/0000-0002-8322-117X"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]},{"id":"https://openalex.org/I4210121626","display_name":"Signal Processing (United States)","ror":"https://ror.org/021gzyw51","country_code":"US","type":"company","lineage":["https://openalex.org/I4210121626"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"Bin Yang","raw_affiliation_strings":["Institute of Signal Processing and System Theory, University of Stuttgart"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Signal Processing and System Theory, University of Stuttgart","institution_ids":["https://openalex.org/I100066346","https://openalex.org/I4210121626"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8588,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.89498574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"296","last_page":"300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9994000196456909,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9994000196456909,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9896000027656555,"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/T10603","display_name":"Smart Grid Energy Management","score":0.9646000266075134,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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":0.7282240986824036},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.6777514815330505},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6599922180175781},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6465517282485962},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.6271054744720459},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5910281538963318},{"id":"https://openalex.org/keywords/co-training","display_name":"Co-training","score":0.5626163482666016},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.5286645889282227},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4868737757205963},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.44855552911758423},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38820594549179077},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3536398410797119},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.347683310508728}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7282240986824036},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.6777514815330505},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6599922180175781},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6465517282485962},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.6271054744720459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5910281538963318},{"id":"https://openalex.org/C2776959682","wikidata":"https://www.wikidata.org/wiki/Q17005296","display_name":"Co-training","level":3,"score":0.5626163482666016},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.5286645889282227},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4868737757205963},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.44855552911758423},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38820594549179077},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3536398410797119},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.347683310508728},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2017.8081216","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2017.8081216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1580375566","https://openalex.org/W1673310716","https://openalex.org/W1994042232","https://openalex.org/W1995875735","https://openalex.org/W2085989833","https://openalex.org/W2123910460","https://openalex.org/W2151729265","https://openalex.org/W2171671120","https://openalex.org/W2951911250","https://openalex.org/W6637131181","https://openalex.org/W6936597892"],"related_works":["https://openalex.org/W2133556223","https://openalex.org/W2949671220","https://openalex.org/W2098708659","https://openalex.org/W2797776314","https://openalex.org/W4303683898","https://openalex.org/W1505796919","https://openalex.org/W2041453872","https://openalex.org/W2378187833","https://openalex.org/W2087783760","https://openalex.org/W121244246"],"abstract_inverted_index":{"Supervised":[0],"event-based":[1,118],"NILM":[2,119],"systems":[3],"usually":[4],"require":[5],"a":[6,24,37],"large":[7],"set":[8,39,84],"of":[9,22,27,40,60,70,80,95],"labeled":[10,41,61],"training":[11,45,62,83,104,144,149],"data":[12],"to":[13,54,98,136,147],"achieve":[14,137],"high":[15,138],"classification":[16,114,139],"accuracies.":[17],"To":[18],"minimize":[19],"the":[20,50,57,78,81,86,93,100,112],"cost":[21],"labeling":[23],"sufficient":[25],"amount":[26],"events,":[28],"active":[29,72,151],"learning":[30,73],"can":[31,64],"be":[32,55,65],"employed.":[33],"By":[34],"using":[35],"only":[36,49],"small":[38],"samples":[42,53,63,145],"for":[43,102],"initial":[44,82,103],"followed":[46],"by":[47],"selecting":[48],"most":[51],"informative":[52],"labeled,":[56],"total":[58],"number":[59],"reduced":[66],"significantly.":[67],"The":[68],"performance":[69],"an":[71,117],"system":[74],"strongly":[75],"depends":[76],"on":[77,111,131],"choice":[79],"and":[85,128],"used":[87,124],"query":[88,109],"strategy.":[89],"We":[90],"thus":[91],"investigated":[92],"impact":[94],"different":[96],"methods":[97],"select":[99],"dataset":[101],"as":[105,107],"well":[106],"various":[108],"strategies":[110],"resulting":[113],"accuracy":[115],"in":[116],"framework.":[120],"For":[121],"evaluation":[122],"we":[123,133],"two":[125],"datasets,":[126],"BLUED":[127],"ISS":[129],"kitchen,":[130],"which":[132],"were":[134],"able":[135],"accuracies":[140],"with":[141],"significantly":[142],"less":[143],"compared":[146],"conventional":[148],"without":[150],"learning.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}