{"id":"https://openalex.org/W4411949818","doi":"https://doi.org/10.1109/vnc64509.2025.11054248","title":"Data Matters: The Case of Predicting Mobile Cellular Traffic","display_name":"Data Matters: The Case of Predicting Mobile Cellular Traffic","publication_year":2025,"publication_date":"2025-06-02","ids":{"openalex":"https://openalex.org/W4411949818","doi":"https://doi.org/10.1109/vnc64509.2025.11054248"},"language":"en","primary_location":{"id":"doi:10.1109/vnc64509.2025.11054248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vnc64509.2025.11054248","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Vehicular Networking Conference (VNC)","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/A5021239027","display_name":"Natalia Vesselinova","orcid":null},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Natalia Vesselinova","raw_affiliation_strings":["Aalto University,Department of Mathematics and Systems Analysis,Finland"],"affiliations":[{"raw_affiliation_string":"Aalto University,Department of Mathematics and Systems Analysis,Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114638623","display_name":"Matti Harjula","orcid":null},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Matti Harjula","raw_affiliation_strings":["Aalto University,Department of Mathematics and Systems Analysis,Finland"],"affiliations":[{"raw_affiliation_string":"Aalto University,Department of Mathematics and Systems Analysis,Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021402082","display_name":"Pauliina Ilmonen","orcid":"https://orcid.org/0000-0002-8992-0553"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Pauliina Ilmonen","raw_affiliation_strings":["Aalto University,Department of Mathematics and Systems Analysis,Finland"],"affiliations":[{"raw_affiliation_string":"Aalto University,Department of Mathematics and Systems Analysis,Finland","institution_ids":["https://openalex.org/I9927081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021239027"],"corresponding_institution_ids":["https://openalex.org/I9927081"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14503817,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9708999991416931,"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":0.9708999991416931,"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":0.6915685534477234},{"id":"https://openalex.org/keywords/cellular-network","display_name":"Cellular network","score":0.45877349376678467},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.30729854106903076}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6915685534477234},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.45877349376678467},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.30729854106903076}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vnc64509.2025.11054248","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vnc64509.2025.11054248","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Vehicular Networking Conference (VNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321108","display_name":"Academy of Finland","ror":"https://ror.org/05k73zm37"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W902862941","https://openalex.org/W1964717191","https://openalex.org/W1965377726","https://openalex.org/W1983883318","https://openalex.org/W2123673584","https://openalex.org/W2137851090","https://openalex.org/W2157112852","https://openalex.org/W2162657189","https://openalex.org/W2345352344","https://openalex.org/W2799789854","https://openalex.org/W3047104333","https://openalex.org/W3123191313","https://openalex.org/W4206755733","https://openalex.org/W4210585986","https://openalex.org/W4226020628","https://openalex.org/W4293095037","https://openalex.org/W4384934710","https://openalex.org/W4390100479","https://openalex.org/W4401995317","https://openalex.org/W4404872680","https://openalex.org/W4406354358","https://openalex.org/W6852580235","https://openalex.org/W6869258864"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Accurate":[0],"predictions":[1],"of":[2,22,28,54],"base":[3,118],"stations\u2019":[4],"traffic":[5,96],"load":[6,78,120],"are":[7,138],"essential":[8],"to":[9,66,72,98,114],"mobile":[10],"cellular":[11,37,77,115],"operators":[12],"and":[13,25,34,56,93,110,135],"their":[14],"users":[15],"as":[16,52,128,130],"they":[17],"support":[18],"the":[19,74],"efficient":[20],"use":[21,94],"network":[23,38,116],"resources":[24],"allow":[26],"delivery":[27],"services":[29],"that":[30,105],"sustain":[31],"smart":[32,91],"cities":[33],"roads.":[35],"Traditionally,":[36],"time-series":[39],"have":[40,60],"been":[41,61],"considered":[42],"for":[43],"this":[44,86],"prediction":[45,100,121],"task.":[46],"More":[47],"recently,":[48],"exogenous":[49],"factors":[50],"such":[51],"points":[53],"interest":[55],"other":[57],"environmental":[58],"knowledge":[59],"explored":[62],"too.":[63],"In":[64,85],"contrast":[65],"incorporating":[67],"external":[68],"factors,":[69],"we":[70,88],"propose":[71],"learn":[73],"processes":[75],"underlying":[76],"generation":[79],"by":[80,106,127],"employing":[81,107],"population":[82],"dynamics":[83],"data.":[84],"study,":[87],"focus":[89],"on":[90,140],"roads":[92],"road":[95,108],"measures":[97],"improve":[99],"accuracy.":[101],"Comprehensive":[102],"experiments":[103],"demonstrate":[104],"flow":[109],"speed,":[111],"in":[112],"addition":[113],"metrics,":[117],"station":[119],"errors":[122],"can":[123],"be":[124],"substantially":[125],"reduced,":[126],"much":[129],"56.5%.":[131],"The":[132],"code,":[133],"visualizations":[134],"extensive":[136],"results":[137],"available":[139],"https://github.com/nvassileva/DataMatters.":[141]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
