{"id":"https://openalex.org/W2507376018","doi":"https://doi.org/10.1145/2905055.2905232","title":"Performance Evaluation of Classifiers on WISDM Dataset for Human Activity Recognition","display_name":"Performance Evaluation of Classifiers on WISDM Dataset for Human Activity Recognition","publication_year":2016,"publication_date":"2016-03-04","ids":{"openalex":"https://openalex.org/W2507376018","doi":"https://doi.org/10.1145/2905055.2905232","mag":"2507376018"},"language":"en","primary_location":{"id":"doi:10.1145/2905055.2905232","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2905055.2905232","pdf_url":null,"source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies","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/A5066693473","display_name":"K. H. Walse","orcid":"https://orcid.org/0000-0003-3977-3740"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"K. H. Walse","raw_affiliation_strings":["Dept. of Computer Science and Engg., Anuradha Engineering College, Chikhli, India"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Engg., Anuradha Engineering College, Chikhli, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083939803","display_name":"R. V. Dharaskar","orcid":"https://orcid.org/0000-0003-3821-3186"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. V. Dharaskar","raw_affiliation_strings":["Disha Technical Campus, Raipur, CG, India"],"affiliations":[{"raw_affiliation_string":"Disha Technical Campus, Raipur, CG, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055678655","display_name":"V. M. Thakare","orcid":"https://orcid.org/0000-0001-8722-8881"},"institutions":[{"id":"https://openalex.org/I150513749","display_name":"Sant Gadge Baba Amravati University","ror":"https://ror.org/05s8p6g93","country_code":"IN","type":"education","lineage":["https://openalex.org/I150513749"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. M. Thakare","raw_affiliation_strings":["P.G. Dept. of Computer Sci. &amp; Engg., S.G.B. Amravati University, Amravati India"],"affiliations":[{"raw_affiliation_string":"P.G. Dept. of Computer Sci. &amp; Engg., S.G.B. Amravati University, Amravati India","institution_ids":["https://openalex.org/I150513749"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5066693473"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.65747562,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.977400004863739,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.8576587438583374},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.7795599102973938},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7394133806228638},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7304130792617798},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.664025604724884},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5774834752082825},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5331166386604309},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46278125047683716},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4530505836009979},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4441041946411133},{"id":"https://openalex.org/keywords/mobile-phone","display_name":"Mobile phone","score":0.43569517135620117}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.8576587438583374},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.7795599102973938},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7394133806228638},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7304130792617798},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.664025604724884},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5774834752082825},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5331166386604309},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46278125047683716},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4530505836009979},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4441041946411133},{"id":"https://openalex.org/C2777421447","wikidata":"https://www.wikidata.org/wiki/Q17517","display_name":"Mobile phone","level":2,"score":0.43569517135620117},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2905055.2905232","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2905055.2905232","pdf_url":null,"source":null,"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W114217056","https://openalex.org/W173797192","https://openalex.org/W1971130285","https://openalex.org/W2017634428","https://openalex.org/W2043757504","https://openalex.org/W2090805767","https://openalex.org/W2121232806","https://openalex.org/W2400626766","https://openalex.org/W2620505295","https://openalex.org/W7030055075"],"related_works":["https://openalex.org/W2811014843","https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456"],"abstract_inverted_index":{"Mobile":[0],"Phone":[1],"used":[2],"not":[3],"to":[4,58],"be":[5],"matter":[6],"luxury":[7],"only,":[8],"it":[9,54],"has":[10],"become":[11],"a":[12,29,76],"significant":[13],"need":[14],"for":[15],"rapidly":[16],"evolving":[17],"fast":[18],"track":[19],"world.":[20],"In":[21,139],"this":[22],"paper,":[23],"we":[24],"evaluate":[25],"the":[26,65,86],"performance":[27],"of":[28,61,67,85,114,133],"various":[30],"machine":[31],"learning":[32],"classifiers":[33],"on":[34,121],"WISDM":[35],"human":[36],"activity":[37,60],"recognition":[38,79],"dataset":[39],"which":[40],"is":[41,55],"available":[42],"in":[43,52,83],"public":[44],"domain.":[45],"We":[46,70],"show":[47],"that":[48,73],"while":[49],"keeping":[50],"smartphone":[51],"pocket,":[53],"very":[56],"easy":[57],"recognize":[59],"daily":[62],"living":[63],"with":[64,117,130],"help":[66],"built-in":[68],"sensors.":[69],"further":[71],"demonstrated":[72],"by":[74,95],"using":[75,98,135],"proper":[77],"classifier,":[78],"rate":[80],"can":[81],"improve":[82],"most":[84],"activities":[87,142],"more":[88],"than":[89],"96%.":[90],"The":[91],"experiments":[92],"were":[93,109],"performed":[94],"other":[96],"researcher":[97],"Multilayer":[99],"Perceptron":[100],"classifier":[101],"(MLP)":[102],"and":[103,112,119],"random":[104,136],"forest":[105,137],"(RF)":[106],"classifier.":[107,138],"They":[108],"received":[110],"91.7%":[111],"75.9%":[113],"overall":[115,131],"accuracy":[116,132],"MLP":[118],"RF":[120],"impersonal":[122],"data":[123],"respectively.":[124],"Our":[125],"results":[126],"are":[127,143],"much":[128],"better":[129],"98.09%":[134],"addition,":[140],"these":[141],"recognized":[144],"quickly.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
