{"id":"https://openalex.org/W3042625521","doi":"https://doi.org/10.1109/access.2020.3009253","title":"Video Popularity Prediction: An Autoencoder Approach With Clustering","display_name":"Video Popularity Prediction: An Autoencoder Approach With Clustering","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3042625521","doi":"https://doi.org/10.1109/access.2020.3009253","mag":"3042625521"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3009253","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3009253","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09139947.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09139947.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089308956","display_name":"Yu-Tai Lin","orcid":"https://orcid.org/0000-0003-0564-8618"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yu-Tai Lin","raw_affiliation_strings":["Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-0564-8618","affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101526670","display_name":"Chia-Cheng Yen","orcid":"https://orcid.org/0000-0002-8420-9762"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chia-Cheng Yen","raw_affiliation_strings":["Department of Computer Science, University of California at Davis, Davis, USA"],"raw_orcid":"https://orcid.org/0000-0002-8420-9762","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California at Davis, Davis, USA","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025490590","display_name":"Jia-Shung Wang","orcid":"https://orcid.org/0000-0003-2157-6108"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jia-Shung Wang","raw_affiliation_strings":["Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-2157-6108","affiliations":[{"raw_affiliation_string":"Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5089308956"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.784,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.92332233,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"8","issue":null,"first_page":"129285","last_page":"129299"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9976999759674072,"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"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9883000254631042,"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/autoencoder","display_name":"Autoencoder","score":0.8961969614028931},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8361990451812744},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6903982758522034},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6135300993919373},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5573910474777222},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5361658334732056},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5141127705574036},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4369821846485138},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.4345957934856415},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.420968234539032},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3303517997264862}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8961969614028931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8361990451812744},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6903982758522034},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6135300993919373},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5573910474777222},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5361658334732056},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5141127705574036},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4369821846485138},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.4345957934856415},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.420968234539032},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3303517997264862},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3009253","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3009253","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09139947.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:efea74e3c1ec4a3aa02e385083e28470","is_oa":true,"landing_page_url":"https://doaj.org/article/efea74e3c1ec4a3aa02e385083e28470","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 129285-129299 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3009253","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3009253","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09139947.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3500011999","display_name":null,"funder_award_id":"MOST 104-2221-E-007-017","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3042625521.pdf","grobid_xml":"https://content.openalex.org/works/W3042625521.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1486317198","https://openalex.org/W1690919088","https://openalex.org/W1720514416","https://openalex.org/W1959608418","https://openalex.org/W2042281163","https://openalex.org/W2056916045","https://openalex.org/W2073459066","https://openalex.org/W2135790056","https://openalex.org/W2137245235","https://openalex.org/W2253995343","https://openalex.org/W2525443997","https://openalex.org/W2548339725","https://openalex.org/W2583674722","https://openalex.org/W2616576833","https://openalex.org/W2899348982","https://openalex.org/W2900229157","https://openalex.org/W2904119337","https://openalex.org/W2923964967","https://openalex.org/W2963611429","https://openalex.org/W2964316331","https://openalex.org/W4293568373","https://openalex.org/W4299286960","https://openalex.org/W6640963894","https://openalex.org/W6668990524","https://openalex.org/W6692935382","https://openalex.org/W6729413687","https://openalex.org/W6780248173","https://openalex.org/W7070499600"],"related_works":["https://openalex.org/W2970845521","https://openalex.org/W2772628444","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W1484355083","https://openalex.org/W3008845055","https://openalex.org/W2098758514","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622"],"abstract_inverted_index":{"Autoencoders":[0],"implemented":[1],"by":[2,134],"artificial":[3],"neural":[4],"networks":[5],"(ANNs)":[6],"are":[7],"utilized":[8],"to":[9,90,173],"learn":[10],"the":[11,47,79,92,104,111,114,127,163,167,177,184,198,205],"latent":[12],"space":[13],"representation":[14],"of":[15,46,106,113,154,180,207],"data":[16],"in":[17,27,77,83,147,162,176,202],"an":[18,84,98],"unsupervised":[19],"manner,":[20],"and":[21,131,196],"they":[22],"have":[23,38],"been":[24],"widely":[25],"used":[26,161],"recommender":[28,67],"systems.":[29,68],"For":[30],"instance,":[31],"several":[32],"collaborative":[33,48],"denoising":[34],"autoencoder":[35,66,99,116,143],"(CDAE)":[36],"models":[37],"shown":[39],"that":[40,45,109,122],"their":[41],"performance":[42,112,185],"gains":[43],"outperform":[44],"filtering":[49],"based":[50,100],"(CF-based)":[51],"models.":[52],"In":[53,88],"this":[54],"work,":[55],"a":[56,71,208],"near-optimal":[57],"Top-K":[58,80,149,156,199],"forecasting":[59,210],"solution":[60],"is":[61],"proposed":[62,142,192],"for":[63,166],"our":[64,123,141,191],"advanced":[65],"We":[69,137],"propose":[70,97],"method":[72,124,193],"which":[73],"utilizes":[74],"CDAE":[75],"model":[76,144],"predicting":[78,148,155],"popular":[81,150,157,200],"videos":[82,158,201],"upcoming":[85],"time":[86],"period.":[87],"order":[89],"improve":[91],"prediction":[93],"accuracy,":[94],"we":[95],"also":[96],"recommendation":[101],"algorithm":[102],"with":[103,145,204],"help":[105,206],"K-means":[107],"clustering":[108,146],"upgrades":[110],"original":[115],"model.":[117,211],"The":[118,152],"experimental":[119],"results":[120],"show":[121],"increases":[125],"significantly":[126],"Average":[128],"Precision":[129],"(AP)":[130],"Recall":[132],"values":[133],"nearly":[135],"30%.":[136],"then":[138],"further":[139],"utilize":[140],"videos.":[151],"applications":[153],"can":[159],"be":[160,188],"video":[164],"delivery":[165],"Mobile":[168],"Edge":[169],"Computing":[170],"(MEC)":[171],"environment":[172],"avoid":[174],"bottleneck":[175],"constricted":[178],"capacity":[179],"backhaul":[181],"link.":[182],"Namely,":[183],"gain":[186],"will":[187],"upgraded":[189],"if":[190],"precisely":[194],"predicts":[195],"caches":[197],"advance":[203],"better":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
