{"id":"https://openalex.org/W2978018511","doi":"https://doi.org/10.1109/iccchina.2019.8855954","title":"Impact of Prediction Uncertainty of Popularity Distribution on Proactive Caching","display_name":"Impact of Prediction Uncertainty of Popularity Distribution on Proactive Caching","publication_year":2019,"publication_date":"2019-08-01","ids":{"openalex":"https://openalex.org/W2978018511","doi":"https://doi.org/10.1109/iccchina.2019.8855954","mag":"2978018511"},"language":"en","primary_location":{"id":"doi:10.1109/iccchina.2019.8855954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccchina.2019.8855954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/CIC International Conference on Communications in China (ICCC)","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/A5072358579","display_name":"Pengyu Cong","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pengyu Cong","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049975562","display_name":"Kaiqiang Qi","orcid":"https://orcid.org/0000-0001-7647-2555"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiqiang Qi","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082950698","display_name":"Chenyang Yang","orcid":"https://orcid.org/0000-0003-0058-0765"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyang Yang","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072358579"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.5305,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.69490418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"747","last_page":"752"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":1.0,"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"}},{"id":"https://openalex.org/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.9850999712944031,"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"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9807000160217285,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/movielens","display_name":"MovieLens","score":0.943737268447876},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8463939428329468},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.5716168880462646},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4683382511138916},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.440681517124176},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.42611241340637207},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.41419267654418945},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41168588399887085},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3042182922363281},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.2794252634048462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2794148921966553},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.2538702189922333},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.17494148015975952}],"concepts":[{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.943737268447876},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8463939428329468},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.5716168880462646},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4683382511138916},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.440681517124176},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.42611241340637207},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.41419267654418945},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41168588399887085},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3042182922363281},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.2794252634048462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2794148921966553},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.2538702189922333},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.17494148015975952},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccchina.2019.8855954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccchina.2019.8855954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/CIC International Conference on Communications in China (ICCC)","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":21,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1972738071","https://openalex.org/W2219888463","https://openalex.org/W2415391790","https://openalex.org/W2425152312","https://openalex.org/W2516631548","https://openalex.org/W2769242936","https://openalex.org/W2771556079","https://openalex.org/W2784459845","https://openalex.org/W2902818012","https://openalex.org/W2903523957","https://openalex.org/W2963092844","https://openalex.org/W2963355846","https://openalex.org/W2963465792","https://openalex.org/W2963805280","https://openalex.org/W2964121744","https://openalex.org/W2964150361","https://openalex.org/W2988575175","https://openalex.org/W3122800475","https://openalex.org/W6631190155","https://openalex.org/W6748208652"],"related_works":["https://openalex.org/W2398491113","https://openalex.org/W2794657157","https://openalex.org/W2219888463","https://openalex.org/W3045147512","https://openalex.org/W2022984797","https://openalex.org/W2075329139","https://openalex.org/W4384919653","https://openalex.org/W2982694712","https://openalex.org/W3096631722","https://openalex.org/W2016618979"],"abstract_inverted_index":{"Proactive":[0],"caching":[1,25,147],"at":[2],"wireless":[3,14],"edge":[4],"can":[5,78],"reduce":[6],"back":[7],"haul":[8],"traffic":[9,15],"load":[10],"or":[11],"even":[12],"offload":[13],"with":[16,167],"periodical":[17],"popularity":[18,52,96],"distribution":[19],"prediction.":[20],"The":[21,127,142],"gain":[22],"from":[23],"proactive":[24,146],"highly":[26],"depends":[27],"on":[28,53,97],"the":[29,32,45,68,80,92,98,100,108,116,124,150,158,172,175,179,185,189,195,203,207,215],"uncertainty":[30,49,129,155],"of":[31,47,50,83,94,145,153,221],"prediction,":[33,65,99],"which":[34,121],"however":[35],"is":[36,119,178,210],"not":[37,131],"well":[38],"understood.":[39],"In":[40],"this":[41,57],"paper,":[42],"we":[43,59],"analyze":[44],"impact":[46,93],"prediction":[48,128,154],"dynamic":[51,95],"probabilistic":[54],"caching.":[55],"To":[56,90],"end,":[58],"employ":[60],"two":[61,101,159,222],"neural":[62],"networks":[63],"for":[64,85,88,157,164],"and":[66,73,139,162,199],"consider":[67],"often-used":[69],"MovieLens":[70,117,173],"1M":[71],"dataset":[72,76,118],"a":[74,219],"real":[75,102,160],"that":[77,115,182],"capture":[79,123],"request":[81],"behavior":[82],"users":[84],"Youku":[86,190],"videos":[87],"evaluation.":[89],"understand":[91],"datasets":[103,161],"are":[104],"shuffled":[105],"to":[106,184],"obtain":[107],"corresponding":[109],"static":[110],"datasets.":[111],"Simulation":[112],"results":[113],"show":[114],"near-static,":[120],"cannot":[122],"cold-start":[125],"problem.":[126],"includes":[130],"only":[132],"additive":[133,176,200,216],"error,":[134],"but":[135],"also":[136],"miss":[137,192],"alarm":[138,193],"false":[140],"alarm.":[141],"performance":[143,186,197],"loss":[144,198,205],"induced":[148],"by":[149],"three":[151],"types":[152],"differs":[156,163],"base":[165],"stations":[166],"different":[168],"cache":[169,208],"sizes.":[170],"For":[171,188,212],"dataset,":[174,191],"error":[177,201],"key":[180],"factor":[181],"leads":[183],"loss.":[187],"incurs":[194,202],"most":[196],"least":[204],"when":[206],"size":[209],"large.":[211],"both":[213],"datasets,":[214],"errors":[217],"follow":[218],"summation":[220],"Gaussian":[223],"distributions.":[224]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
