{"id":"https://openalex.org/W2998874759","doi":"https://doi.org/10.1109/mci.2019.2954641","title":"Mining Mobile Intelligence for Wireless Systems: A Deep Neural Network Approach","display_name":"Mining Mobile Intelligence for Wireless Systems: A Deep Neural Network Approach","publication_year":2020,"publication_date":"2020-01-10","ids":{"openalex":"https://openalex.org/W2998874759","doi":"https://doi.org/10.1109/mci.2019.2954641","mag":"2998874759"},"language":"en","primary_location":{"id":"doi:10.1109/mci.2019.2954641","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mci.2019.2954641","pdf_url":null,"source":{"id":"https://openalex.org/S104797584","display_name":"IEEE Computational Intelligence Magazine","issn_l":"1556-603X","issn":["1556-603X","1556-6048"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Computational Intelligence Magazine","raw_type":"journal-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/A5020194895","display_name":"Han Hu","orcid":"https://orcid.org/0000-0001-7532-0496"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Hu","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100603421","display_name":"Zhi Liu","orcid":"https://orcid.org/0000-0003-0537-4522"},"institutions":[{"id":"https://openalex.org/I1298590031","display_name":"Shizuoka University","ror":"https://ror.org/01w6wtk13","country_code":"JP","type":"education","lineage":["https://openalex.org/I1298590031"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhi Liu","raw_affiliation_strings":["College of Engineering, Shizuoka University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Engineering, Shizuoka University, Japan","institution_ids":["https://openalex.org/I1298590031"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044674658","display_name":"Jianping An","orcid":"https://orcid.org/0000-0002-6441-9711"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianping An","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.5865,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.98109692,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"15","issue":"1","first_page":"24","last_page":"31"},"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":0.9991000294685364,"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":0.9991000294685364,"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/T11478","display_name":"Caching and Content Delivery","score":0.9957000017166138,"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":0.9908000230789185,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7168877720832825},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5525151491165161},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5172812938690186},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.4974806606769562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47401174902915955},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.24760594964027405}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7168877720832825},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5525151491165161},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5172812938690186},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.4974806606769562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47401174902915955},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.24760594964027405}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mci.2019.2954641","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mci.2019.2954641","pdf_url":null,"source":{"id":"https://openalex.org/S104797584","display_name":"IEEE Computational Intelligence Magazine","issn_l":"1556-603X","issn":["1556-603X","1556-6048"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Computational Intelligence Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2246840391","display_name":null,"funder_award_id":"3052019041","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1530780135","https://openalex.org/W1916769834","https://openalex.org/W1973454958","https://openalex.org/W1987228002","https://openalex.org/W1992735035","https://openalex.org/W2009251196","https://openalex.org/W2009654461","https://openalex.org/W2020669710","https://openalex.org/W2034415518","https://openalex.org/W2045522464","https://openalex.org/W2052169465","https://openalex.org/W2057415864","https://openalex.org/W2074937974","https://openalex.org/W2090978188","https://openalex.org/W2123805908","https://openalex.org/W2343361823","https://openalex.org/W2511747249","https://openalex.org/W2533246774","https://openalex.org/W2546679426","https://openalex.org/W2562141967","https://openalex.org/W2593227599","https://openalex.org/W2593389066","https://openalex.org/W2602020924","https://openalex.org/W2605633941","https://openalex.org/W2739652405","https://openalex.org/W2775033655","https://openalex.org/W2775051529","https://openalex.org/W2783206562","https://openalex.org/W2784189955","https://openalex.org/W2796244678","https://openalex.org/W2803557526","https://openalex.org/W2890884249","https://openalex.org/W2894543895","https://openalex.org/W2897781255","https://openalex.org/W2963334314","https://openalex.org/W2964164085","https://openalex.org/W4299734264"],"related_works":["https://openalex.org/W2386387936","https://openalex.org/W3107474891","https://openalex.org/W1629725936","https://openalex.org/W3001020386","https://openalex.org/W644753246","https://openalex.org/W2379462128","https://openalex.org/W2159443810","https://openalex.org/W1532348048","https://openalex.org/W4234410389","https://openalex.org/W3162911039"],"abstract_inverted_index":{"Wireless":[0],"big":[1,46],"data":[2,47,92],"contain":[3],"valuable":[4],"information":[5],"on":[6,45,136],"users'":[7],"behaviors":[8],"and":[9,16,30,52,54,70,97,150,176,209,233,241],"preferences,":[10],"which":[11],"can":[12],"drive":[13],"the":[14,63,106,112,124,140,154,159,165,171,179,186,191,196,201,205,215,219,229],"design":[15,51],"optimization":[17],"for":[18,143,181],"wireless":[19,35,49,144,224],"systems.":[20,36],"The":[21],"fundamental":[22],"issue":[23],"is":[24],"how":[25,137],"to":[26,59,86,93,104,138,163,184,199,213],"mine":[27],"mobile":[28,107,141],"intelligence":[29,142],"further":[31],"incorporate":[32],"them":[33,61],"into":[34],"To":[37],"this":[38,40],"end,":[39],"article":[41],"discusses":[42],"two":[43,134],"challenges":[44],"based":[48],"system":[50],"optimization,":[53],"proposes":[55],"a":[56,78,94,99,222],"unified":[57],"framework":[58],"tackle":[60],"with":[62,128,221],"help":[64],"of":[65,90,167,173],"Deep":[66],"Neural":[67],"Networks":[68],"(DNNs)":[69],"online":[71,129],"learning":[72,116,130],"techniques.":[73],"In":[74,153,190],"particular,":[75],"we":[76,132,157,194,226],"propose":[77],"DNN":[79,126,161],"architecture":[80,127],"by":[81],"incorporating":[82],"an":[83],"embedding":[84],"layer":[85],"project":[87],"different":[88],"types":[89],"raw":[91],"latent":[95],"space":[96],"utilize":[98,158,195],"regression":[100],"or":[101],"classification":[102],"function":[103],"predict":[105,164,200],"access":[108,216],"pattern.":[109],"It":[110],"outperforms":[111],"best":[113],"traditional":[114],"machine":[115],"algorithm":[117],"(76%":[118],"vs.":[119],"63%)":[120],"significantly.":[121],"Moreover,":[122],"combining":[123],"proposed":[125,160,197],"techniques,":[131],"show":[133,227],"cases":[135],"apply":[139],"video":[145,148,151,182,187,231],"applications,":[146],"including":[147],"adaption":[149],"pre-fetching.":[152],"former":[155],"case,":[156],"method":[162,198],"dynamics":[166],"user":[168,202],"count":[169],"within":[170],"coverage":[172],"base":[174,207],"stations,":[175,208],"adaptively":[177],"adjust":[178],"bitrate":[180],"streaming":[183],"improve":[185],"watching":[188],"experience.":[189],"latter":[192],"one,":[193],"trajectory,":[203],"i.e.,":[204],"associated":[206],"conduct":[210],"content":[211],"prefetching":[212],"reduce":[214],"latency.":[217],"Evaluating":[218],"performance":[220],"real":[223],"dataset,":[225],"that":[228],"perceived":[230],"QoE":[232],"cache":[234],"hit":[235],"ratio":[236],"are":[237],"greatly":[238],"improved":[239],"(0.7db":[240],"25%":[242],"respectively).":[243]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
