{"id":"https://openalex.org/W2806613807","doi":"https://doi.org/10.1145/3195106.3195146","title":"Clustering Analysis of Human Behavior Based on Mobile Phone Sensor Data","display_name":"Clustering Analysis of Human Behavior Based on Mobile Phone Sensor Data","publication_year":2018,"publication_date":"2018-02-26","ids":{"openalex":"https://openalex.org/W2806613807","doi":"https://doi.org/10.1145/3195106.3195146","mag":"2806613807"},"language":"en","primary_location":{"id":"doi:10.1145/3195106.3195146","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3195106.3195146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 10th International Conference on Machine Learning and Computing","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/A5100440604","display_name":"Jue Wang","orcid":"https://orcid.org/0000-0002-3641-3136"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jue Wang","raw_affiliation_strings":["Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, School of Computer Science, BUPT, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, School of Computer Science, BUPT, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031877096","display_name":"Zhibin Huang","orcid":"https://orcid.org/0000-0002-7579-6969"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibin Huang","raw_affiliation_strings":["Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, School of Computer Science, BUPT, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, School of Computer Science, BUPT, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055816670","display_name":"Huanyuan Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanyuan Xu","raw_affiliation_strings":["Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, School of Computer Science, BUPT, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Intelligent Telecommunication Software and Multimedia, School of Computer Science, BUPT, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050564435","display_name":"Zilu Kang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zilu Kang","raw_affiliation_strings":["Institute of Internet of Things, Information Sciences Academy, CETC, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Internet of Things, Information Sciences Academy, CETC, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100440604"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.7341,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.79461556,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"64","last_page":"68"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9797999858856201,"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"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9797999858856201,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9444000124931335,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9262999892234802,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.9222862720489502},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.7935692071914673},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.7576526999473572},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.727724552154541},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.7173705101013184},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.6786994934082031},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.6537845134735107},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.581784188747406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5193568468093872},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.5110548734664917},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5030226111412048},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49997949600219727},{"id":"https://openalex.org/keywords/determining-the-number-of-clusters-in-a-data-set","display_name":"Determining the number of clusters in a data set","score":0.47610363364219666}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.9222862720489502},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.7935692071914673},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.7576526999473572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.727724552154541},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.7173705101013184},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.6786994934082031},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.6537845134735107},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.581784188747406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5193568468093872},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.5110548734664917},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5030226111412048},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49997949600219727},{"id":"https://openalex.org/C149872217","wikidata":"https://www.wikidata.org/wiki/Q5265701","display_name":"Determining the number of clusters in a data set","level":5,"score":0.47610363364219666}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3195106.3195146","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3195106.3195146","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 10th International Conference on Machine Learning and Computing","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":11,"referenced_works":["https://openalex.org/W1536826708","https://openalex.org/W1588091815","https://openalex.org/W1629143244","https://openalex.org/W2103664294","https://openalex.org/W2155893237","https://openalex.org/W2162549501","https://openalex.org/W2314305063","https://openalex.org/W2472331206","https://openalex.org/W2529970009","https://openalex.org/W2592696565","https://openalex.org/W2599475929"],"related_works":["https://openalex.org/W2014841791","https://openalex.org/W2353158678","https://openalex.org/W2394193399","https://openalex.org/W2809859387","https://openalex.org/W2387373525","https://openalex.org/W2054669762","https://openalex.org/W2355615404","https://openalex.org/W2163563073","https://openalex.org/W1987613674","https://openalex.org/W2389934482"],"abstract_inverted_index":{"In":[0,47],"recent":[1],"years,":[2],"some":[3],"of":[4,22,53,58,100,141],"the":[5,9,51,92,112,120,127,139,147,167],"methods":[6,24,61],"based":[7],"on":[8],"deep":[10],"learning":[11],"theory":[12],"to":[13,36,49,64,90,118,125,145],"identify":[14],"human":[15],"activities":[16],"have":[17],"been":[18],"proposed.":[19],"However,":[20],"most":[21],"these":[23],"are":[25,62,88],"not":[26],"suitable":[27],"for":[28],"hardware":[29],"with":[30],"limited":[31],"resources":[32],"when":[33,138],"it":[34],"comes":[35],"rapid":[37],"real-time":[38],"analysis":[39,42,60],"considering":[40],"its":[41],"complexity":[43],"and":[44,84,163,173],"data":[45,102],"scale.":[46],"order":[48],"minimize":[50],"amount":[52,99],"input":[54,101],"data,":[55],"a":[56,104],"variety":[57],"clustering":[59,69,73,76,79,82,86,114,158,161,165],"proposed":[63],"address":[65],"this":[66],"issue.":[67],"Six":[68],"algorithms":[70],"including":[71],"K-means":[72],"algorithm,":[74,77,80,159,166],"K-mode":[75,164],"CLARANS":[78,160],"BIRCH":[81],"algorithm":[83,87,115,162],"DBSCAN":[85,113],"implemented":[89],"reduce":[91,119],"feature":[93,121],"scale,":[94],"results":[95],"in":[96],"greatly":[97],"reduced":[98,144],"while":[103],"high":[105],"recognition":[106],"accuracy":[107,129,148,169],"is":[108,116,143,170],"still":[109,150],"ensured.":[110],"When":[111],"used":[117],"dimension":[122],"from":[123],"561":[124],"145,":[126],"classification":[128,168],"drops":[130],"merely":[131],"less":[132],"than":[133],"2%,":[134],"reaching":[135],"93.58%.":[136],"Even":[137],"number":[140],"features":[142],"100,":[146],"can":[149],"be":[151],"maintained":[152],"at":[153],"91.38%.":[154],"By":[155],"using":[156],"Birch":[157],"89.75%,":[171],"85.4%":[172],"76.28%":[174],"respectively.":[175]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}