{"id":"https://openalex.org/W2014058952","doi":"https://doi.org/10.1109/icmlc.2013.6890755","title":"The conversion from similarity for mobile life-log to euclidean distance","display_name":"The conversion from similarity for mobile life-log to euclidean distance","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2014058952","doi":"https://doi.org/10.1109/icmlc.2013.6890755","mag":"2014058952"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2013.6890755","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2013.6890755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Machine Learning and Cybernetics","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/A5111654966","display_name":"Ye-Teng An","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ye-Teng An","raw_affiliation_strings":["School of Computer Science, Tianjin University, China","School of Computer Science, Tianjin University, China#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Computer Science, Tianjin University, China#TAB#","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113572046","display_name":"Chung-Nam Pak","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chung-Nam Pak","raw_affiliation_strings":["Col. of Information Sci., D.P.R.K","School of Computer Science, Tianjin University, China","School of Computer Science, Tianjin University, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Col. of Information Sci., D.P.R.K","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Computer Science, Tianjin University, China#TAB#","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736532","display_name":"Zhiyong Feng","orcid":"https://orcid.org/0000-0001-8158-7453"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi-Yong Feng","raw_affiliation_strings":["School of Computer Science, Tianjin University, China","School of Computer Science, Tianjin University, China#TAB#"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]},{"raw_affiliation_string":"School of Computer Science, Tianjin University, China#TAB#","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109249612","display_name":"Sung-Nam Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I344333522","display_name":"Kim Chaek University of Technology","ror":"https://ror.org/04vew1z32","country_code":"KP","type":"education","lineage":["https://openalex.org/I344333522"]}],"countries":["KP"],"is_corresponding":false,"raw_author_name":"Sung-Nam Kim","raw_affiliation_strings":["Col. of Information Sci., D.P.R.K","Col. of Information Sci., Kim Chaek Univ. of Technol., D.P.R.K"],"affiliations":[{"raw_affiliation_string":"Col. of Information Sci., D.P.R.K","institution_ids":[]},{"raw_affiliation_string":"Col. of Information Sci., Kim Chaek Univ. of Technol., D.P.R.K","institution_ids":["https://openalex.org/I344333522"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029954479","display_name":"Hyok-Chol Choe","orcid":null},"institutions":[{"id":"https://openalex.org/I344333522","display_name":"Kim Chaek University of Technology","ror":"https://ror.org/04vew1z32","country_code":"KP","type":"education","lineage":["https://openalex.org/I344333522"]}],"countries":["KP"],"is_corresponding":false,"raw_author_name":"Hyok-Chol Choe","raw_affiliation_strings":["Col. of Information Sci., D.P.R.K","Col. of Information Sci., Kim Chaek Univ. of Technol., D.P.R.K"],"affiliations":[{"raw_affiliation_string":"Col. of Information Sci., D.P.R.K","institution_ids":[]},{"raw_affiliation_string":"Col. of Information Sci., Kim Chaek Univ. of Technol., D.P.R.K","institution_ids":["https://openalex.org/I344333522"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5111654966"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08627152,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"1087","last_page":"1091"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9678999781608582,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9656000137329102,"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/euclidean-distance","display_name":"Euclidean distance","score":0.8049086928367615},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7575728893280029},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7055982351303101},{"id":"https://openalex.org/keywords/euclidean-space","display_name":"Euclidean space","score":0.6153296232223511},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5964698791503906},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.5519355535507202},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5284923315048218},{"id":"https://openalex.org/keywords/impossibility","display_name":"Impossibility","score":0.48445868492126465},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4491536021232605},{"id":"https://openalex.org/keywords/minkowski-distance","display_name":"Minkowski distance","score":0.44113877415657043},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.41824620962142944},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.4127439558506012},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4106203317642212},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3789157271385193},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.340579628944397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3315127491950989},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3247649073600769},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.15363571047782898},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08439725637435913}],"concepts":[{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.8049086928367615},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7575728893280029},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7055982351303101},{"id":"https://openalex.org/C186450821","wikidata":"https://www.wikidata.org/wiki/Q17295","display_name":"Euclidean space","level":2,"score":0.6153296232223511},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5964698791503906},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.5519355535507202},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5284923315048218},{"id":"https://openalex.org/C2776261394","wikidata":"https://www.wikidata.org/wiki/Q315562","display_name":"Impossibility","level":2,"score":0.48445868492126465},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4491536021232605},{"id":"https://openalex.org/C110765721","wikidata":"https://www.wikidata.org/wiki/Q2414361","display_name":"Minkowski distance","level":3,"score":0.44113877415657043},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.41824620962142944},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.4127439558506012},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4106203317642212},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3789157271385193},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.340579628944397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3315127491950989},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3247649073600769},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.15363571047782898},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08439725637435913},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc.2013.6890755","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2013.6890755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Machine Learning and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production","score":0.4399999976158142}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W975333032","https://openalex.org/W1563419623","https://openalex.org/W1978394996","https://openalex.org/W1980876331","https://openalex.org/W2012886963","https://openalex.org/W2032624390","https://openalex.org/W2061681393","https://openalex.org/W2069821836","https://openalex.org/W2099957958","https://openalex.org/W2118216287","https://openalex.org/W4236643049","https://openalex.org/W6677557080"],"related_works":["https://openalex.org/W2934869655","https://openalex.org/W1992732116","https://openalex.org/W4210963094","https://openalex.org/W2585552969","https://openalex.org/W3123672120","https://openalex.org/W1642991110","https://openalex.org/W3102221223","https://openalex.org/W3008082054","https://openalex.org/W3203505583","https://openalex.org/W2105228010"],"abstract_inverted_index":{"Mobile":[0,12],"devices":[1,13],"are":[2,20],"widely":[3],"used":[4],"due":[5],"to":[6,22,64],"their":[7],"convenience.":[8],"However,":[9,47],"information":[10],"from":[11,137],"always":[14],"contains":[15],"the":[16,26,37,49,57,61,67,76,96,99,103,106,117,125,133,148,153],"semantic":[17],"contents,":[18],"which":[19],"hard":[21],"be":[23],"analyzed":[24],"by":[25,109],"Data":[27],"Mining":[28],"methods":[29],"such":[30],"as":[31],"clustering.":[32],"Therefore,":[33],"some":[34],"researchers":[35],"calculate":[36,75],"relative":[38,62],"similarity":[39,63,77,97],"based":[40,85],"on":[41,86,105],"k-means":[42],"clustering":[43],"or":[44],"association":[45],"rules.":[46],"without":[48],"consideration":[50],"of":[51,53,59,88,135,145,152],"features":[52,101],"non-Euclidean":[54,100,121],"data,":[55,92],"and":[56,78,93,150],"impossibility":[58],"converting":[60],"Euclidean":[65,107],"space,":[66],"accuracy":[68],"is":[69],"low.":[70],"In":[71],"this":[72],"paper,":[73],"we":[74,115],"Term":[79],"Frequency":[80,83],"Inverse":[81],"Document":[82],"(TF-IDF)":[84],"analysis":[87],"mobile":[89,138],"life":[90],"log":[91],"then":[94],"convert":[95],"with":[98,142],"into":[102],"distance":[104],"space":[108],"pseudo-Euclidean":[110],"embedding.":[111],"As":[112],"a":[113],"result,":[114],"realize":[116],"data":[118,130],"mining":[119],"for":[120],"data.":[122],"We":[123],"apply":[124],"proposed":[126,154],"method":[127],"in":[128],"collecting":[129],"that":[131],"reflect":[132],"life-patterns":[134,144],"students":[136,146],"devices.":[139],"Experimental":[140],"comparisons":[141],"real":[143],"show":[147],"feasibility":[149],"effectiveness":[151],"method.":[155]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
