{"id":"https://openalex.org/W4309651445","doi":"https://doi.org/10.1145/3557915.3560996","title":"How do you go where?","display_name":"How do you go where?","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4309651445","doi":"https://doi.org/10.1145/3557915.3560996"},"language":"en","primary_location":{"id":"doi:10.1145/3557915.3560996","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3557915.3560996","pdf_url":null,"source":{"id":"https://openalex.org/S4363608995","display_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2210.04095","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073847508","display_name":"Ye Hong","orcid":"https://orcid.org/0000-0002-8996-3748"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Ye Hong","raw_affiliation_strings":["ETH Zurich, Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028853860","display_name":"Henry Martin","orcid":"https://orcid.org/0000-0002-0456-8539"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Henry Martin","raw_affiliation_strings":["ETH Zurich, Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004721499","display_name":"Martin Raubal","orcid":"https://orcid.org/0000-0001-5951-6835"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Martin Raubal","raw_affiliation_strings":["ETH Zurich, Zurich, Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I35440088"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"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":1.0,"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":1.0,"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/T10298","display_name":"Urban Transport and Accessibility","score":0.9968000054359436,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9796000123023987,"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/computer-science","display_name":"Computer science","score":0.8151699900627136},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5694053769111633},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5618149638175964},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.5380254983901978},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.5090791583061218},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47896650433540344},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.46884453296661377},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46326711773872375},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4468306005001068},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4323994815349579},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4185882806777954},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41446158289909363},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.10732203722000122}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8151699900627136},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5694053769111633},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5618149638175964},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.5380254983901978},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.5090791583061218},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47896650433540344},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.46884453296661377},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46326711773872375},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4468306005001068},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4323994815349579},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4185882806777954},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41446158289909363},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.10732203722000122},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3557915.3560996","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3557915.3560996","pdf_url":null,"source":{"id":"https://openalex.org/S4363608995","display_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2210.04095","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.04095","pdf_url":"https://arxiv.org/pdf/2210.04095","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2210.04095","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.04095","pdf_url":"https://arxiv.org/pdf/2210.04095","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3425616736","display_name":null,"funder_award_id":"1-008062","funder_id":"https://openalex.org/F4320321942","funder_display_name":"Hasler Stiftung"}],"funders":[{"id":"https://openalex.org/F4320321942","display_name":"Hasler Stiftung","ror":"https://ror.org/04m3t9183"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1964461063","https://openalex.org/W1987228002","https://openalex.org/W2001672212","https://openalex.org/W2017566989","https://openalex.org/W2018455582","https://openalex.org/W2065985231","https://openalex.org/W2069810468","https://openalex.org/W2073122003","https://openalex.org/W2103269714","https://openalex.org/W2133400794","https://openalex.org/W2139153982","https://openalex.org/W2148731873","https://openalex.org/W2168685189","https://openalex.org/W2194775991","https://openalex.org/W2278892783","https://openalex.org/W2281120853","https://openalex.org/W2499609862","https://openalex.org/W2539781657","https://openalex.org/W2569045317","https://openalex.org/W2788114581","https://openalex.org/W2799727164","https://openalex.org/W2892126244","https://openalex.org/W2900312347","https://openalex.org/W2950726468","https://openalex.org/W2954843234","https://openalex.org/W2963028112","https://openalex.org/W2971517005","https://openalex.org/W3021364764","https://openalex.org/W3080501557","https://openalex.org/W3102247173","https://openalex.org/W3118697270","https://openalex.org/W3129749388","https://openalex.org/W3163356969","https://openalex.org/W3173363430","https://openalex.org/W3177318507","https://openalex.org/W3198380387","https://openalex.org/W3202610094","https://openalex.org/W3217016897","https://openalex.org/W4206718713","https://openalex.org/W4221074052","https://openalex.org/W4221095962","https://openalex.org/W4226028809","https://openalex.org/W4312779995","https://openalex.org/W4319336084","https://openalex.org/W4385245566","https://openalex.org/W6928803863"],"related_works":["https://openalex.org/W3162200841","https://openalex.org/W2109940557","https://openalex.org/W2466832359","https://openalex.org/W2586280620","https://openalex.org/W2805505483","https://openalex.org/W2334071950","https://openalex.org/W2384744344","https://openalex.org/W3125011624","https://openalex.org/W4233932308","https://openalex.org/W2899848438"],"abstract_inverted_index":{"Predicting":[0],"the":[1,21,39,65,68,81,107,130,142,152,156,163,169,181,189,195],"next":[2,40,69,114,170,191],"visited":[3],"location":[4,41,115,184],"of":[5,25,67,144,183,206,209,220],"an":[6,42,75,136],"individual":[7,43],"is":[8,18,72,225],"a":[9,32,119,202],"key":[10],"problem":[11],"in":[12,60,127,173,212],"human":[13,213],"mobility":[14,214],"analysis,":[15],"as":[16,74],"it":[17],"required":[19],"for":[20,129,201],"personalization":[22],"and":[23,51,93,123,151,223],"optimization":[24],"sustainable":[26],"transport":[27],"options.":[28],"Here,":[29],"we":[30,86,160],"propose":[31],"transformer":[33],"decoder-based":[34],"neural":[35],"network":[36],"to":[37,78,90],"predict":[38],"will":[44],"visit":[45],"based":[46],"on":[47,155],"historical":[48],"locations,":[49],"time,":[50],"travel":[52,70,148,192,210],"modes,":[53],"which":[54],"are":[55],"behaviour":[56,211],"dimensions":[57,208],"often":[58],"overlooked":[59],"previous":[61],"work.":[62],"In":[63],"particular,":[64],"prediction":[66,116,157,172,185,215],"mode":[71,149,171,193],"designed":[73],"auxiliary":[76,153],"task":[77,154],"help":[79],"guide":[80],"network's":[82],"learning.":[83],"For":[84],"evaluation,":[85],"apply":[87],"this":[88],"approach":[89],"two":[91,131],"large-scale":[92],"long-term":[94],"GPS":[95],"tracking":[96],"datasets":[97],"involving":[98],"more":[99,203],"than":[100],"600":[101],"individuals.":[102],"Our":[103],"experiments":[104,224],"show":[105,199],"that":[106,140,180],"proposed":[108],"method":[109],"significantly":[110,187],"outperforms":[111],"other":[112],"state-of-the-art":[113],"methods":[117],"by":[118,194],"large":[120],"margin":[121],"(8.05%":[122],"5.60%":[124],"relative":[125],"increase":[126],"F1-score":[128],"datasets,":[132],"respectively).":[133],"We":[134],"conduct":[135],"extensive":[137],"ablation":[138],"study":[139],"quantifies":[141],"influence":[143],"considering":[145],"temporal":[146],"features,":[147],"information,":[150],"results.":[158],"Moreover,":[159],"experimentally":[161],"determine":[162],"performance":[164,182],"upper":[165],"bound":[166],"when":[167],"including":[168],"our":[174,177,221],"model.":[175],"Finally,":[176],"analysis":[178],"indicates":[179],"varies":[186],"with":[188],"chosen":[190],"individual.":[196],"These":[197],"results":[198],"potential":[200],"systematic":[204],"consideration":[205],"additional":[207],"tasks.":[216],"The":[217],"source":[218],"code":[219],"model":[222],"available":[226],"at":[227],"https://github.com/mie-lab/location-mode-prediction.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2022-11-29T00:00:00"}