{"id":"https://openalex.org/W3006991141","doi":"https://doi.org/10.1109/bigdata47090.2019.9006301","title":"Personalized POI Embedding for Successive POI Recommendation with Large-scale Smart Card Data","display_name":"Personalized POI Embedding for Successive POI Recommendation with Large-scale Smart Card Data","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3006991141","doi":"https://doi.org/10.1109/bigdata47090.2019.9006301","mag":"3006991141"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","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/A5100386828","display_name":"Jin\u2010Young Kim","orcid":"https://orcid.org/0000-0003-3319-4887"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jin-Young Kim","raw_affiliation_strings":["Dept. of Computer Science, Yonsei University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051343528","display_name":"Kyung-Hyun Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyung-Hyun Lim","raw_affiliation_strings":["Dept. of Computer Science, Yonsei University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108081550","display_name":"Sung\u2010Bae Cho","orcid":"https://orcid.org/0000-0002-7027-2429"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sung-Bae Cho","raw_affiliation_strings":["Dept. of Computer Science, Yonsei University, Seoul, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7253,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.82356312,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3583","last_page":"3589"},"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":0.9995999932289124,"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":0.9995999932289124,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9947999715805054,"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/T11478","display_name":"Caching and Content Delivery","score":0.9034000039100647,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7183789014816284},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5524746179580688},{"id":"https://openalex.org/keywords/smart-card","display_name":"Smart card","score":0.5047281980514526},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4464442729949951},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24447187781333923},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.16259858012199402},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07854399085044861},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.07641547918319702}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7183789014816284},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5524746179580688},{"id":"https://openalex.org/C110406131","wikidata":"https://www.wikidata.org/wiki/Q41349","display_name":"Smart card","level":2,"score":0.5047281980514526},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4464442729949951},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24447187781333923},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.16259858012199402},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07854399085044861},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.07641547918319702}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006301","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","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":36,"referenced_works":["https://openalex.org/W1505093402","https://openalex.org/W1520352740","https://openalex.org/W1546409232","https://openalex.org/W1598796236","https://openalex.org/W1614298861","https://openalex.org/W2007043321","https://openalex.org/W2062785849","https://openalex.org/W2131744502","https://openalex.org/W2205235818","https://openalex.org/W2513361716","https://openalex.org/W2515671155","https://openalex.org/W2523438800","https://openalex.org/W2539781657","https://openalex.org/W2567312369","https://openalex.org/W2573719245","https://openalex.org/W2584122106","https://openalex.org/W2604411573","https://openalex.org/W2771679022","https://openalex.org/W2789519372","https://openalex.org/W2791295797","https://openalex.org/W2807855639","https://openalex.org/W2907639449","https://openalex.org/W2931222964","https://openalex.org/W2950577311","https://openalex.org/W2964057288","https://openalex.org/W4205848394","https://openalex.org/W6632885370","https://openalex.org/W6635679246","https://openalex.org/W6636510571","https://openalex.org/W6679775712","https://openalex.org/W6688089849","https://openalex.org/W6728864075","https://openalex.org/W6731415707","https://openalex.org/W6732130061","https://openalex.org/W6736108819","https://openalex.org/W6749325611"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2081900870","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2120234551","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857"],"abstract_inverted_index":{"Point-of-interest":[0],"(POI)":[1],"recommendation":[2,126],"can":[3,187],"help":[4],"providing":[5],"better":[6],"user":[7,30,55,116,149],"experience,":[8],"and":[9,63,111,115,150,206,211,226],"provide":[10],"users":[11,104],"with":[12],"third-party":[13],"information":[14,42],"about":[15],"restaurant":[16],"or":[17,46,52],"entertainment.":[18],"There":[19],"are":[20,215],"several":[21,136],"studies":[22],"to":[23,35,61,80,122,135,139,158,192],"predict":[24],"the":[25,29,85,91,153,160,163,167,171,178,183,193,218,221,232,236],"next":[26,164],"POI":[27,70,82,92,100,114,125,147,180,186,198,243],"where":[28],"will":[31],"go":[32],"so":[33],"as":[34,44],"recommend":[36,81],"appropriate":[37],"services.":[38],"They":[39],"use":[40],"additional":[41,96],"such":[43],"text":[45],"location":[47],"for":[48,69,105,128],"more":[49],"precise":[50],"prediction,":[51],"manually":[53],"define":[54],"patterns.":[56],"However,":[57],"it":[58,119],"is":[59,120,156,174,182],"costly":[60],"collect":[62],"analyze":[64],"large":[65],"amounts":[66],"of":[67,162,170,220,235],"data":[68,93,101],"recommendation.":[71,199],"In":[72],"this":[73],"paper,":[74],"we":[75,132,230],"propose":[76],"a":[77,145],"novel":[78],"method":[79,169],"by":[83],"extracting":[84],"personalized":[86,113,197],"movement":[87],"pattern":[88],"only":[89],"from":[90,108],"without":[94],"any":[95],"information.":[97],"We":[98],"collected":[99],"ofl.":[102],"5M":[103],"six":[106],"months":[107],"smart":[109],"card,":[110],"produce":[112],"embedding.":[117],"Since":[118],"hard":[121],"construct":[123],"one":[124],"model":[127,155,173,202,223,238],"1.5":[129],"million":[130],"people,":[131],"divide":[133],"them":[134],"groups":[137],"according":[138,191],"their":[140],"simple":[141],"mobility":[142],"pattern.":[143],"Given":[144],"previous":[146],"sequence,":[148],"group":[151],"id,":[152],"proposed":[154,172,201,237],"trained":[157],"maximize":[159],"probability":[161],"POI.":[165],"Although":[166],"learning":[168],"simple,":[175],"even":[176],"if":[177],"given":[179],"sequence":[181],"same,":[184],"successive":[185],"be":[188],"predicted":[189],"differently":[190],"user,":[194],"resulting":[195],"in":[196,208],"The":[200],"achieves":[203],"73.64%,":[204],"88.65%,":[205],"91.54%":[207],"top-1,":[209],"3":[210],"5":[212],"accuracies":[213],"which":[214],"higher":[216],"than":[217],"performance":[219,234],"baseline":[222],"(59.48%,":[224],"75.85%,":[225],"80.1%,":[227],"respectively).":[228],"Besides,":[229],"verify":[231],"embedding":[233],"through":[239],"arithmetic":[240],"operations":[241],"between":[242],"vectors.":[244]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
