{"id":"https://openalex.org/W4408100914","doi":"https://doi.org/10.1109/acai63924.2024.10899499","title":"Sequential Recommendation via Temporal Data Augmentation and Fourier Convolution","display_name":"Sequential Recommendation via Temporal Data Augmentation and Fourier Convolution","publication_year":2024,"publication_date":"2024-12-20","ids":{"openalex":"https://openalex.org/W4408100914","doi":"https://doi.org/10.1109/acai63924.2024.10899499"},"language":"en","primary_location":{"id":"doi:10.1109/acai63924.2024.10899499","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acai63924.2024.10899499","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 7th International Conference on Algorithms, Computing and Artificial Intelligence (ACAI)","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/A5101311916","display_name":"Junming Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junming Luo","raw_affiliation_strings":["School of Computer Science South China Normal University,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science South China Normal University,Guangzhou,China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068724826","display_name":"Tinghua Zhang","orcid":"https://orcid.org/0000-0002-6977-1140"},"institutions":[{"id":"https://openalex.org/I4210113818","display_name":"China Electronic Product Reliability and Environmental Test Institute","ror":"https://ror.org/01f4k3b46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210113818"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tinghua Zhang","raw_affiliation_strings":["China Electronics Product Reliability and Environmental Testing Research Institute,Software and Systems Research Department,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Electronics Product Reliability and Environmental Testing Research Institute,Software and Systems Research Department,Guangzhou,China","institution_ids":["https://openalex.org/I4210113818"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083051145","display_name":"Ke Jin","orcid":"https://orcid.org/0000-0003-4666-565X"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Jin","raw_affiliation_strings":["School of Computer Science South China Normal University,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science South China Normal University,Guangzhou,China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102988293","display_name":"Weihao Yu","orcid":"https://orcid.org/0000-0003-0727-4744"},"institutions":[{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]},{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihao Yu","raw_affiliation_strings":["Research Institute of China Telecom Corporation Ltd,Network technology research department,Guangzhou,China"],"raw_orcid":"https://orcid.org/0000-0003-0727-4744","affiliations":[{"raw_affiliation_string":"Research Institute of China Telecom Corporation Ltd,Network technology research department,Guangzhou,China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069858475","display_name":"Jin Huang","orcid":"https://orcid.org/0000-0003-2285-5248"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Huang","raw_affiliation_strings":["School of Computer Science South China Normal University,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science South China Normal University,Guangzhou,China","institution_ids":["https://openalex.org/I187400657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.35050796,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9302999973297119,"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"}},"topics":[{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9302999973297119,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9194999933242798,"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/convolution","display_name":"Convolution (computer science)","score":0.7285565137863159},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7049059867858887},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.5000243186950684},{"id":"https://openalex.org/keywords/overlap\u2013add-method","display_name":"Overlap\u2013add method","score":0.442608505487442},{"id":"https://openalex.org/keywords/discrete-time-fourier-transform","display_name":"Discrete-time Fourier transform","score":0.4292648732662201},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.340310275554657},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3343077600002289},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.2667212188243866},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.1825067400932312},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1786091923713684},{"id":"https://openalex.org/keywords/fractional-fourier-transform","display_name":"Fractional Fourier transform","score":0.07008251547813416},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.06438079476356506}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.7285565137863159},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7049059867858887},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.5000243186950684},{"id":"https://openalex.org/C181002996","wikidata":"https://www.wikidata.org/wiki/Q1611641","display_name":"Overlap\u2013add method","level":5,"score":0.442608505487442},{"id":"https://openalex.org/C122444316","wikidata":"https://www.wikidata.org/wiki/Q1440048","display_name":"Discrete-time Fourier transform","level":5,"score":0.4292648732662201},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.340310275554657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3343077600002289},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.2667212188243866},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.1825067400932312},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1786091923713684},{"id":"https://openalex.org/C76563020","wikidata":"https://www.wikidata.org/wiki/Q4817582","display_name":"Fractional Fourier transform","level":4,"score":0.07008251547813416},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.06438079476356506},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acai63924.2024.10899499","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acai63924.2024.10899499","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 7th International Conference on Algorithms, Computing and Artificial Intelligence (ACAI)","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":26,"referenced_works":["https://openalex.org/W2512965516","https://openalex.org/W2783272285","https://openalex.org/W2783944588","https://openalex.org/W2798385737","https://openalex.org/W2809307135","https://openalex.org/W2963367478","https://openalex.org/W2964044287","https://openalex.org/W2964296635","https://openalex.org/W2964352502","https://openalex.org/W2984100107","https://openalex.org/W2996931760","https://openalex.org/W3031475799","https://openalex.org/W3033630125","https://openalex.org/W3045200674","https://openalex.org/W3065542300","https://openalex.org/W3133849783","https://openalex.org/W3156844209","https://openalex.org/W3206127589","https://openalex.org/W4206660090","https://openalex.org/W4220974940","https://openalex.org/W4280513135","https://openalex.org/W4296591843","https://openalex.org/W4382240261","https://openalex.org/W4385245566","https://openalex.org/W4385270206","https://openalex.org/W4396758715"],"related_works":["https://openalex.org/W2232752250","https://openalex.org/W2171853844","https://openalex.org/W2888715284","https://openalex.org/W2385421611","https://openalex.org/W2196313388","https://openalex.org/W2053055950","https://openalex.org/W3034644587","https://openalex.org/W827829366","https://openalex.org/W4224987185","https://openalex.org/W1570542763"],"abstract_inverted_index":{"Sequence":[0],"recommendation":[1,34],"aims":[2],"to":[3,76,105,127],"predict":[4],"user":[5,43,85],"preferences":[6],"by":[7,96],"modeling":[8],"users'":[9],"dynamic":[10],"historical":[11],"behaviors.":[12],"In":[13],"recent":[14],"years,":[15],"advancements":[16],"in":[17,53],"sequence":[18,28,33,62,133],"deep":[19],"learning":[20],"models":[21],"such":[22],"as":[23],"Transformer":[24],"have":[25],"significantly":[26],"enhanced":[27],"rec-ommendation.":[29],"However,":[30],"most":[31],"existing":[32],"approaches":[35],"primarily":[36],"focus":[37],"on":[38,123,139],"the":[39,47,59,79,107,124,129,144,148],"sequential":[40],"information":[41],"of":[42,61,150],"behaviors":[44],"while":[45],"neglecting":[46],"critical":[48],"temporal":[49,82],"information.":[50],"Additionally,":[51],"noise":[52,109],"interaction":[54],"records":[55],"has":[56],"consistently":[57],"im-peded":[58],"performance":[60],"recommendations.":[63],"To":[64],"address":[65],"these":[66],"two":[67],"shortcomings,":[68],"we":[69,88,117,136],"propose":[70],"a":[71,119],"model":[72],"named":[73],"TAFC4Rec.":[74],"First,":[75],"better":[77,113],"exploit":[78],"relationship":[80],"between":[81],"infor-mation":[83],"and":[84,131,143],"interest":[86],"changes,":[87],"improve":[89],"three":[90],"classical":[91],"stochastic":[92],"data":[93,103,130],"augmentation":[94],"methods":[95],"incorporating":[97],"time":[98],"interval":[99],"calculations.":[100],"Furthermore,":[101],"following":[102],"augmentation,":[104],"enhance":[106],"encoder's":[108],"filtering":[110],"capability":[111],"for":[112],"handling":[114],"augmented":[115],"data,":[116],"design":[118],"convolutional":[120],"structure":[121],"based":[122],"Fourier":[125],"transform":[126],"denoise":[128],"capture":[132],"features.":[134],"Finally,":[135],"conducted":[137],"experiments":[138],"four":[140],"real-world":[141],"datasets,":[142],"experimental":[145],"results":[146],"demonstrate":[147],"effectiveness":[149],"our":[151],"model.":[152]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
