{"id":"https://openalex.org/W2341752517","doi":"https://doi.org/10.1145/2837126.2837140","title":"ClusterNN","display_name":"ClusterNN","publication_year":2015,"publication_date":"2015-12-11","ids":{"openalex":"https://openalex.org/W2341752517","doi":"https://doi.org/10.1145/2837126.2837140","mag":"2341752517"},"language":"en","primary_location":{"id":"doi:10.1145/2837126.2837140","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2837126.2837140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Advances in Mobile Computing and Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10059/2044","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022809696","display_name":"Sulaimon Adebayo Bashir","orcid":"https://orcid.org/0000-0001-8690-3953"},"institutions":[{"id":"https://openalex.org/I522815984","display_name":"Robert Gordon University","ror":"https://ror.org/04f0qj703","country_code":"GB","type":"education","lineage":["https://openalex.org/I522815984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sulaimon Bashir","raw_affiliation_strings":["Robert Gordon University, Aberdeen, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robert Gordon University, Aberdeen, UK","institution_ids":["https://openalex.org/I522815984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031534210","display_name":"Daniel C. Doolan","orcid":"https://orcid.org/0000-0002-8964-7200"},"institutions":[{"id":"https://openalex.org/I522815984","display_name":"Robert Gordon University","ror":"https://ror.org/04f0qj703","country_code":"GB","type":"education","lineage":["https://openalex.org/I522815984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Daniel Doolan","raw_affiliation_strings":["Robert Gordon University, Aberdeen, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robert Gordon University, Aberdeen, UK","institution_ids":["https://openalex.org/I522815984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040494006","display_name":"Andrei Petrovski","orcid":"https://orcid.org/0000-0002-0987-2791"},"institutions":[{"id":"https://openalex.org/I522815984","display_name":"Robert Gordon University","ror":"https://ror.org/04f0qj703","country_code":"GB","type":"education","lineage":["https://openalex.org/I522815984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Andrei Petrovski","raw_affiliation_strings":["Robert Gordon University, Aberdeen, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robert Gordon University, Aberdeen, UK","institution_ids":["https://openalex.org/I522815984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I522815984"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"263","last_page":"267"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9677000045776367,"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/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9645000100135803,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8090442419052124},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6809185743331909},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6354049444198608},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5469111204147339},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5393794178962708},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.48854860663414},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46333375573158264},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.45612776279449463},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.450917512178421},{"id":"https://openalex.org/keywords/mobile-phone","display_name":"Mobile phone","score":0.44725045561790466},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.4221423864364624},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3833667039871216},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08555224537849426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8090442419052124},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6809185743331909},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6354049444198608},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5469111204147339},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5393794178962708},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.48854860663414},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46333375573158264},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.45612776279449463},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.450917512178421},{"id":"https://openalex.org/C2777421447","wikidata":"https://www.wikidata.org/wiki/Q17517","display_name":"Mobile phone","level":2,"score":0.44725045561790466},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.4221423864364624},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3833667039871216},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08555224537849426},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/2837126.2837140","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2837126.2837140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Advances in Mobile Computing and Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:www.open-access.bcu.ac.uk:4027","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402654","display_name":"BCU Open Access Repository (Birmingham City University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I12870472","host_organization_name":"Birmingham City University","host_organization_lineage":["https://openalex.org/I12870472"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Book Section"},{"id":"pmh:oai:openair.rgu.ac.uk:10059/2044","is_oa":true,"landing_page_url":"http://hdl.handle.net/10059/2044","pdf_url":null,"source":{"id":"https://openalex.org/S4306400814","display_name":"Open Access Institutional Repository at Robert Gordon University (Robert Gordon University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I522815984","host_organization_name":"Robert Gordon University","host_organization_lineage":["https://openalex.org/I522815984"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference publications"}],"best_oa_location":{"id":"pmh:oai:openair.rgu.ac.uk:10059/2044","is_oa":true,"landing_page_url":"http://hdl.handle.net/10059/2044","pdf_url":null,"source":{"id":"https://openalex.org/S4306400814","display_name":"Open Access Institutional Repository at Robert Gordon University (Robert Gordon University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I522815984","host_organization_name":"Robert Gordon University","host_organization_lineage":["https://openalex.org/I522815984"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference publications"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W128941585","https://openalex.org/W1528532344","https://openalex.org/W2017634428","https://openalex.org/W2054242744","https://openalex.org/W2056591916","https://openalex.org/W2078439954","https://openalex.org/W2097906225","https://openalex.org/W2132691216","https://openalex.org/W2133990480","https://openalex.org/W2162555816","https://openalex.org/W2604721075","https://openalex.org/W2621549321","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W3195649134","https://openalex.org/W2281498195","https://openalex.org/W2017526120","https://openalex.org/W4298130764","https://openalex.org/W2610664080","https://openalex.org/W2188304107","https://openalex.org/W2804364458","https://openalex.org/W2761510556","https://openalex.org/W2132641928","https://openalex.org/W4310225030"],"abstract_inverted_index":{"Mobile":[0],"activity":[1,42,162],"recognition":[2,43,163],"from":[3,119],"sensor":[4],"data":[5],"is":[6,24,33,54,78],"based":[7,36],"on":[8,50,149],"supervised":[9],"learning":[10,89],"algorithms.":[11],"Many":[12],"algorithms":[13,23],"have":[14],"been":[15,45],"proposed":[16,157],"for":[17,56,70,81,125,139],"this":[18],"task.":[19],"One":[20],"of":[21,100,116,155],"such":[22],"the":[25,62,74,93,101,110,144,150,169],"K-nearest":[26],"neighbour":[27,146],"(KNN)":[28],"algorithm.":[29,172],"However,":[30],"since":[31],"KNN":[32,57,171],"an":[34,87],"instance":[35],"algorithm":[37,147],"its":[38],"use":[39],"in":[40,68],"mobile":[41,82,151,161],"has":[44],"limited":[46],"to":[47,58,96,109,112],"offline":[48],"evaluation":[49,154],"collected":[51],"data.":[52,131],"This":[53,77],"because":[55],"work":[59],"well":[60],"all":[61],"training":[63,94],"instances":[64,142],"must":[65],"be":[66,137],"kept":[67],"memory":[69],"similarity":[71,126],"measurement":[72,127],"with":[73,128],"test":[75],"instance.":[76],"however":[79],"prohibitive":[80],"environment.":[83],"Therefore,":[84],"we":[85],"propose":[86],"unsupervised":[88],"step":[90,148],"that":[91],"reduces":[92],"set":[95,115],"a":[97,114],"proportional":[98],"size":[99],"original":[102],"dataset.":[103],"The":[104],"novel":[105],"approach":[106,158],"applies":[107],"clustering":[108],"dataset":[111,164],"obtain":[113],"micro":[117],"clusters":[118],"which":[120],"cluster":[121],"characteristics":[122],"are":[123],"extracted":[124],"new":[129,141],"unseen":[130],"These":[132],"reduced":[133],"representative":[134],"sets":[135],"can":[136],"used":[138],"classifying":[140],"using":[143,159],"nearest":[145],"phone.":[152],"Experimental":[153],"our":[156],"real":[160],"shows":[165],"improved":[166],"result":[167],"over":[168],"basic":[170]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2016-06-24T00:00:00"}
