{"id":"https://openalex.org/W3034710094","doi":"https://doi.org/10.1145/3397271.3401125","title":"A Generic Network Compression Framework for Sequential Recommender Systems","display_name":"A Generic Network Compression Framework for Sequential Recommender Systems","publication_year":2020,"publication_date":"2020-07-25","ids":{"openalex":"https://openalex.org/W3034710094","doi":"https://doi.org/10.1145/3397271.3401125","mag":"3034710094"},"language":"en","primary_location":{"id":"doi:10.1145/3397271.3401125","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397271.3401125","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","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/A5100714902","display_name":"Yang Sun","orcid":"https://orcid.org/0000-0002-8661-100X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Sun","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081665927","display_name":"Fajie Yuan","orcid":"https://orcid.org/0000-0001-8452-9929"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fajie Yuan","raw_affiliation_strings":["Tencent, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052437722","display_name":"Min Yang","orcid":"https://orcid.org/0000-0001-9714-5545"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Yang","raw_affiliation_strings":["SIAT, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SIAT, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043967561","display_name":"Guoao Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoao Wei","raw_affiliation_strings":["SIAT, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SIAT, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhou Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhou Zhao","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100675843","display_name":"Duo Liu","orcid":"https://orcid.org/0000-0002-3040-2065"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Duo Liu","raw_affiliation_strings":["SIAT, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SIAT, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1299","last_page":"1308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9891999959945679,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.988099992275238,"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/computer-science","display_name":"Computer science","score":0.8371784687042236},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.8177533149719238},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.743442952632904},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46465033292770386},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4572654664516449},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4552251100540161},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.45084479451179504},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.435314416885376},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4339744448661804},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42893338203430176},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3754848539829254},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28155916929244995}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8371784687042236},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8177533149719238},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.743442952632904},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46465033292770386},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4572654664516449},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4552251100540161},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.45084479451179504},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.435314416885376},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4339744448661804},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42893338203430176},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3754848539829254},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28155916929244995},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3397271.3401125","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397271.3401125","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","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":27,"referenced_works":["https://openalex.org/W587794757","https://openalex.org/W2042281163","https://openalex.org/W2045882407","https://openalex.org/W2058641082","https://openalex.org/W2118722179","https://openalex.org/W2143719855","https://openalex.org/W2194775991","https://openalex.org/W2233116163","https://openalex.org/W2253884061","https://openalex.org/W2469952266","https://openalex.org/W2539247542","https://openalex.org/W2564792523","https://openalex.org/W2619206542","https://openalex.org/W2654637199","https://openalex.org/W2783272285","https://openalex.org/W2789142637","https://openalex.org/W2808847742","https://openalex.org/W2902040508","https://openalex.org/W2963367478","https://openalex.org/W2964044287","https://openalex.org/W2964296635","https://openalex.org/W2964809821","https://openalex.org/W2972367971","https://openalex.org/W2989395463","https://openalex.org/W3045200674","https://openalex.org/W3101023724","https://openalex.org/W3102888024"],"related_works":["https://openalex.org/W1484355083","https://openalex.org/W2772628444","https://openalex.org/W4220714703","https://openalex.org/W2735929803","https://openalex.org/W2170391450","https://openalex.org/W2098758514","https://openalex.org/W3008845055","https://openalex.org/W2041004656","https://openalex.org/W135044020","https://openalex.org/W4376854386"],"abstract_inverted_index":{"Sequential":[0],"recommender":[1,21],"systems":[2],"(SRS)":[3],"have":[4],"become":[5],"the":[6,42,65,85,115,122,134,137,167,174],"key":[7],"technology":[8],"in":[9,80,126,185,198],"capturing":[10],"user's":[11],"dynamic":[12],"interests":[13],"and":[14,46,117,164,197],"generating":[15],"high-quality":[16],"recommendations.":[17],"Current":[18],"state-of-the-art":[19],"sequential":[20,91],"models":[22,53],"are":[23,39,103],"typically":[24],"based":[25],"on":[26],"a":[27,55,89,109,129],"sandwich-structured":[28],"deep":[29,151],"neural":[30,153],"network,":[31],"where":[32,97],"one":[33],"or":[34],"more":[35],"middle":[36,138],"(hidden)":[37],"layers":[38],"placed":[40],"between":[41],"input":[43,116],"embedding":[44],"layer":[45],"output":[47],"softmax":[48,118],"layer.":[49],"In":[50],"general,":[51],"these":[52],"require":[54],"large":[56],"number":[57],"of":[58,136],"parameters":[59,135],"to":[60,113,160,180],"obtain":[61],"optimal":[62],"performance.":[63],"Despite":[64],"effectiveness,":[66],"at":[67],"some":[68],"point,":[69],"further":[70],"increasing":[71],"model":[72,78,100],"size":[73],"may":[74],"be":[75],"harder":[76],"for":[77],"deployment":[79],"resource-constraint":[81],"devices.":[82],"To":[83,132],"resolve":[84],"issues,":[86],"we":[87,106,140,171],"propose":[88,108],"compressed":[90],"recommendation":[92,162],"framework,":[93],"termed":[94],"as":[95],"CpRec,":[96],"two":[98],"generic":[99],"shrinking":[101],"techniques":[102],"employed.":[104],"Specifically,":[105],"first":[107],"block-wise":[110],"adaptive":[111],"decomposition":[112],"approximate":[114],"matrices":[119],"by":[120],"exploiting":[121],"fact":[123],"that":[124,173],"items":[125],"SRS":[127,187],"obey":[128],"long-tailed":[130],"distribution.":[131],"reduce":[133],"layers,":[139],"introduce":[141],"three":[142],"layer-wise":[143],"parameter":[144],"sharing":[145],"schemes.":[146],"We":[147],"instantiate":[148],"CpRec":[149,176,190],"using":[150],"convolutional":[152],"network":[154],"with":[155],"dilated":[156],"kernels":[157],"given":[158],"consideration":[159],"both":[161],"accuracy":[163],"efficiency.":[165],"By":[166],"extensive":[168],"ablation":[169],"studies,":[170],"demonstrate":[172],"proposed":[175],"can":[177],"achieve":[178],"up":[179],"4~8":[181],"times":[182],"compression":[183],"rates":[184],"real-world":[186],"datasets.":[188],"Meanwhile,":[189],"is":[191],"faster":[192],"during":[193],"training":[194],"&":[195],"inference,":[196],"most":[199],"cases":[200],"outperforms":[201],"its":[202],"uncompressed":[203],"counterpart.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}