{"id":"https://openalex.org/W2144685566","doi":"https://doi.org/10.1145/2736277.2741077","title":"Who, What, When, and Where","display_name":"Who, What, When, and Where","publication_year":2015,"publication_date":"2015-05-18","ids":{"openalex":"https://openalex.org/W2144685566","doi":"https://doi.org/10.1145/2736277.2741077","mag":"2144685566"},"language":"en","primary_location":{"id":"doi:10.1145/2736277.2741077","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2736277.2741077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th International Conference on World Wide Web","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/A5001782831","display_name":"Preeti Bhargava","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Preeti Bhargava","raw_affiliation_strings":["University of Maryland, College Park, College Park, MD, USA","University of Maryland, College Park, College Park, MD, USA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"University of Maryland, College Park, College Park, MD, USA;","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113481947","display_name":"Thomas Phan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas Phan","raw_affiliation_strings":["Samsung Research America -- Silicon Valley, San Jose, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Research America -- Silicon Valley, San Jose, CA, USA","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047215778","display_name":"Jiayu Zhou","orcid":"https://orcid.org/0000-0003-4336-6777"},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiayu Zhou","raw_affiliation_strings":["Samsung Research America -- Silicon Valley, San Jose, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Research America -- Silicon Valley, San Jose, CA, USA","institution_ids":["https://openalex.org/I4210101778"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016727594","display_name":"Juhan Lee","orcid":"https://orcid.org/0000-0003-4910-2596"},"institutions":[{"id":"https://openalex.org/I4210101778","display_name":"Samsung (United States)","ror":"https://ror.org/01bfbvm65","country_code":"US","type":"company","lineage":["https://openalex.org/I2250650973","https://openalex.org/I4210101778"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Juhan Lee","raw_affiliation_strings":["Samsung Research America -- Silicon Valley, San Jose, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Research America -- Silicon Valley, San Jose, CA, USA","institution_ids":["https://openalex.org/I4210101778"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.5989,"has_fulltext":false,"cited_by_count":121,"citation_normalized_percentile":{"value":0.96254682,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"130","last_page":"140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.972599983215332,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9542999863624573,"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/recommender-system","display_name":"Recommender system","score":0.7855782508850098},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7714581489562988},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6660096645355225},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.6016483902931213},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6014692187309265},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5240105390548706},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5086411237716675},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4724971354007721},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.470515638589859},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.44798779487609863},{"id":"https://openalex.org/keywords/participatory-sensing","display_name":"Participatory sensing","score":0.4464784562587738},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4381885528564453},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.36688053607940674},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3419615924358368},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1314527988433838},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12133392691612244},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11316409707069397},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.08203169703483582}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7855782508850098},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7714581489562988},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6660096645355225},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.6016483902931213},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6014692187309265},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5240105390548706},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5086411237716675},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4724971354007721},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.470515638589859},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.44798779487609863},{"id":"https://openalex.org/C2779208394","wikidata":"https://www.wikidata.org/wiki/Q7140460","display_name":"Participatory sensing","level":2,"score":0.4464784562587738},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4381885528564453},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.36688053607940674},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3419615924358368},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1314527988433838},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12133392691612244},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11316409707069397},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.08203169703483582},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2736277.2741077","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2736277.2741077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th International Conference on World Wide Web","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1246381107","https://openalex.org/W1565064763","https://openalex.org/W1615057313","https://openalex.org/W1632866817","https://openalex.org/W1652319903","https://openalex.org/W1680797894","https://openalex.org/W1736726159","https://openalex.org/W1758833344","https://openalex.org/W1814521481","https://openalex.org/W1921081011","https://openalex.org/W1970830946","https://openalex.org/W1971040550","https://openalex.org/W2009779426","https://openalex.org/W2013912476","https://openalex.org/W2024165284","https://openalex.org/W2028690229","https://openalex.org/W2052039980","https://openalex.org/W2054141820","https://openalex.org/W2056102005","https://openalex.org/W2061651455","https://openalex.org/W2067193733","https://openalex.org/W2073021764","https://openalex.org/W2078736197","https://openalex.org/W2091917610","https://openalex.org/W2102937240","https://openalex.org/W2103388840","https://openalex.org/W2109102948","https://openalex.org/W2112150227","https://openalex.org/W2117420919","https://openalex.org/W2117587045","https://openalex.org/W2121739212","https://openalex.org/W2126762950","https://openalex.org/W2131147042","https://openalex.org/W2134251598","https://openalex.org/W2159094788","https://openalex.org/W2167143366","https://openalex.org/W2251291469","https://openalex.org/W2404400936","https://openalex.org/W2419656545","https://openalex.org/W2913920413","https://openalex.org/W4233117851","https://openalex.org/W4285719527","https://openalex.org/W6729308270","https://openalex.org/W6824129819"],"related_works":["https://openalex.org/W3109911900","https://openalex.org/W1575318294","https://openalex.org/W4312998587","https://openalex.org/W3080740766","https://openalex.org/W2909865466","https://openalex.org/W2032039661","https://openalex.org/W4386143129","https://openalex.org/W2908124738","https://openalex.org/W2067330905","https://openalex.org/W2000026009"],"abstract_inverted_index":{"Given":[0],"the":[1,77],"abundance":[2],"of":[3,80,170,196],"online":[4],"information":[5,21],"available":[6],"to":[7,49],"mobile":[8],"users,":[9],"particularly":[10],"tourists":[11],"and":[12,22,58,73,115,130,150,161,190],"weekend":[13],"travelers,":[14],"recommender":[15],"systems":[16,61],"that":[17,62,192],"effectively":[18],"filter":[19],"this":[20,109],"suggest":[23],"interesting":[24,36],"participatory":[25],"opportunities":[26],"will":[27],"become":[28],"increasingly":[29],"important.":[30],"Previous":[31],"work":[32],"has":[33],"explored":[34],"recommending":[35],"locations;":[37],"however,":[38],"users":[39],"would":[40,75],"also":[41],"benefit":[42],"from":[43,153,175],"recommendations":[44,65,122],"for":[45,118,123],"activities":[46,72],"in":[47,180],"which":[48,94,145],"participate":[50],"at":[51],"those":[52],"locations":[53],"along":[54],"with":[55,186],"suitable":[56],"times":[57],"days.":[59],"Thus,":[60],"provide":[63],"collaborative":[64,121],"involving":[66],"multiple":[67],"dimensions":[68,85],"such":[69],"as":[70],"location,":[71],"time":[74],"enhance":[76],"overall":[78],"experience":[79],"users.The":[81],"relationship":[82],"among":[83],"these":[84,102],"can":[86,104],"be":[87,105],"modeled":[88],"by":[89,98],"higher-order":[90],"matrices":[91,151],"called":[92],"tensors":[93,103,149],"are":[95],"then":[96],"solved":[97],"tensor":[99,134],"factorization.":[100],"However,":[101],"extremely":[106],"sparse.":[107],"In":[108],"paper,":[110],"we":[111],"present":[112],"a":[113],"system":[114,160],"an":[116,142],"approach":[117,162,185],"performing":[119],"multi-dimensional":[120],"Who":[124],"(User),":[125],"What":[126],"(Activity),":[127],"When":[128],"(Time)":[129],"Where":[131],"(Location),":[132],"using":[133],"factorization":[135],"on":[136,163],"sparse":[137],"user-generated":[138],"data.":[139],"We":[140,157,182],"formulate":[141],"objective":[143],"function":[144],"simultaneously":[146],"factorizes":[147],"coupled":[148],"constructed":[152],"heterogeneous":[154],"data":[155,167],"sources.":[156],"evaluate":[158],"our":[159,184],"large-scale":[164],"real":[165],"world":[166],"sets":[168],"consisting":[169],"588,000":[171],"Flickr":[172],"photos":[173],"collected":[174],"three":[176],"major":[177],"metro":[178],"regions":[179],"USA.":[181],"compare":[183],"several":[187],"state-of-the-art":[188],"baselines":[189],"demonstrate":[191],"it":[193],"outperforms":[194],"all":[195],"them.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":20},{"year":2019,"cited_by_count":28},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":12},{"year":2016,"cited_by_count":14},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}