{"id":"https://openalex.org/W7160430056","doi":"https://doi.org/10.1109/iwqos65803.2025.11506401","title":"A Knowledge-enhanced Hierarchical Graph Transfer Learning Framework for Large-scale Mobile Traffic Prediction","display_name":"A Knowledge-enhanced Hierarchical Graph Transfer Learning Framework for Large-scale Mobile Traffic Prediction","publication_year":2025,"publication_date":"2025-07-02","ids":{"openalex":"https://openalex.org/W7160430056","doi":"https://doi.org/10.1109/iwqos65803.2025.11506401"},"language":null,"primary_location":{"id":"doi:10.1109/iwqos65803.2025.11506401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwqos65803.2025.11506401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/ACM 33rd International Symposium on Quality of Service (IWQoS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5135527912","display_name":"Xing Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Wang","raw_affiliation_strings":["China Mobile Research Institute,JIUTIAN Team,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute,JIUTIAN Team,Beijing,China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135495939","display_name":"Zhiyan Song","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyan Song","raw_affiliation_strings":["China Mobile Research Institute,JIUTIAN Team,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute,JIUTIAN Team,Beijing,China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135496584","display_name":"Zhendong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhendong Wang","raw_affiliation_strings":["China Mobile Research Institute,JIUTIAN Team,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute,JIUTIAN Team,Beijing,China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135457198","display_name":"Kexin Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kexin Yang","raw_affiliation_strings":["China Mobile Research Institute,JIUTIAN Team,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute,JIUTIAN Team,Beijing,China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135463294","display_name":"Chao Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Deng","raw_affiliation_strings":["China Mobile Research Institute,JIUTIAN Team,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute,JIUTIAN Team,Beijing,China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135464013","display_name":"Junlan Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junlan Feng","raw_affiliation_strings":["China Mobile Research Institute,JIUTIAN Team,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute,JIUTIAN Team,Beijing,China","institution_ids":["https://openalex.org/I180662265"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180662265"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.7350999712944031,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.7350999712944031,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13918","display_name":"Advanced Data and IoT Technologies","score":0.057100001722574234,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.03139999881386757,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/transfer-of-learning","display_name":"Transfer of learning","score":0.4625000059604645},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43939998745918274},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.35839998722076416},{"id":"https://openalex.org/keywords/data-transmission","display_name":"Data transmission","score":0.29420000314712524},{"id":"https://openalex.org/keywords/mobile-computing","display_name":"Mobile computing","score":0.28690001368522644},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.27090001106262207}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6607999801635742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48750001192092896},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43939998745918274},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.35839998722076416},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34119999408721924},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3199000060558319},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2906000018119812},{"id":"https://openalex.org/C144543869","wikidata":"https://www.wikidata.org/wiki/Q2738570","display_name":"Mobile computing","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.25929999351501465},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2535000145435333},{"id":"https://openalex.org/C95491727","wikidata":"https://www.wikidata.org/wiki/Q992968","display_name":"Mobile telephony","level":3,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwqos65803.2025.11506401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwqos65803.2025.11506401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/ACM 33rd International Symposium on Quality of Service (IWQoS)","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":5,"referenced_works":["https://openalex.org/W2010670047","https://openalex.org/W2902952649","https://openalex.org/W2914592219","https://openalex.org/W2921319277","https://openalex.org/W4226298073"],"related_works":[],"abstract_inverted_index":{"Large-scale":[0],"mobile":[1,33,61],"traffic":[2,34,62,106],"prediction":[3,24],"is":[4],"critical":[5],"for":[6,27,59],"intelligent":[7],"telecommunication":[8],"networks,":[9],"but":[10],"remains":[11],"challenging":[12],"due":[13],"to":[14,73,90],"complex":[15],"spatial-temporal":[16,77],"patterns":[17],"and":[18,36,55,101],"network":[19,38],"heterogeneity.":[20,39],"Existing":[21],"transfer":[22],"learning-based":[23],"methods,":[25],"tailored":[26],"grid":[28],"data,":[29],"inadequately":[30],"handle":[31],"graph-based":[32],"data":[35],"ignore":[37],"In":[40],"this":[41],"paper,":[42],"we":[43],"propose":[44],"a":[45,67],"Knowledge-enhanced":[46],"Hierarchical":[47],"Graph":[48,70],"Transfer":[49],"Learning":[50],"(KHGTL)":[51],"framework":[52],"integrating":[53],"graph-level":[54],"node-level":[56],"knowledge":[57],"transfer,":[58],"large-scale":[60,105],"prediction.":[63,107],"We":[64],"also":[65],"present":[66],"Spatial-Temporal":[68],"Adaptive":[69],"Convolutional":[71],"Network":[72],"capture":[74],"the":[75],"intricate":[76],"correlations.":[78],"Experiments":[79],"on":[80],"real":[81],"datasets":[82],"show":[83],"KHGTL":[84],"reduces":[85],"MAE":[86],"by":[87],"44.7%":[88],"compared":[89],"baselines,":[91],"outperforms":[92],"full":[93],"supervision":[94],"with":[95],"80%":[96],"faster":[97],"training,":[98],"addressing":[99],"scalability":[100],"efficiency":[102],"challenges":[103],"in":[104]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-05-07T00:00:00"}