{"id":"https://openalex.org/W3088257568","doi":"https://doi.org/10.1145/3383313.3412247","title":"FISSA: Fusing Item Similarity Models with Self-Attention Networks for Sequential Recommendation","display_name":"FISSA: Fusing Item Similarity Models with Self-Attention Networks for Sequential Recommendation","publication_year":2020,"publication_date":"2020-09-19","ids":{"openalex":"https://openalex.org/W3088257568","doi":"https://doi.org/10.1145/3383313.3412247","mag":"3088257568"},"language":"en","primary_location":{"id":"doi:10.1145/3383313.3412247","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383313.3412247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fourteenth ACM Conference on Recommender Systems","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/A5100754187","display_name":"Jing Lin","orcid":"https://orcid.org/0000-0001-6472-9982"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jing Lin","raw_affiliation_strings":["College of Computer Science and Software Engineering Shenzhen University, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering Shenzhen University, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073490832","display_name":"Weike Pan","orcid":"https://orcid.org/0000-0001-6326-9531"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weike Pan","raw_affiliation_strings":["College of Computer Science and Software Engineering Shenzhen University, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering Shenzhen University, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100633979","display_name":"Zhong Ming","orcid":"https://orcid.org/0000-0002-6933-5760"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Ming","raw_affiliation_strings":["College of Computer Science and Software Engineering Shenzhen University, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering Shenzhen University, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100754187"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":11.6859,"has_fulltext":false,"cited_by_count":75,"citation_normalized_percentile":{"value":0.98507676,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"130","last_page":"139"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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":1.0,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9865999817848206,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8225468397140503},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6962119340896606},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6426451206207275},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5544591546058655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5502529144287109},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.496876984834671},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4942896366119385},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.4833642840385437},{"id":"https://openalex.org/keywords/imperfect","display_name":"Imperfect","score":0.47655943036079407},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.4665059447288513},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.462371826171875},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4420098066329956},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34195882081985474},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32776349782943726},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08656033873558044}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8225468397140503},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6962119340896606},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6426451206207275},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5544591546058655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5502529144287109},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.496876984834671},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4942896366119385},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4833642840385437},{"id":"https://openalex.org/C2780310539","wikidata":"https://www.wikidata.org/wiki/Q12547192","display_name":"Imperfect","level":2,"score":0.47655943036079407},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.4665059447288513},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.462371826171875},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4420098066329956},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34195882081985474},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32776349782943726},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08656033873558044},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3383313.3412247","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3383313.3412247","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fourteenth ACM Conference on Recommender Systems","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":54,"referenced_works":["https://openalex.org/W1902237438","https://openalex.org/W1994389483","https://openalex.org/W2027731328","https://openalex.org/W2042281163","https://openalex.org/W2054560962","https://openalex.org/W2055945388","https://openalex.org/W2099866409","https://openalex.org/W2108920354","https://openalex.org/W2138108551","https://openalex.org/W2140310134","https://openalex.org/W2157973827","https://openalex.org/W2171279286","https://openalex.org/W2205235818","https://openalex.org/W2253995343","https://openalex.org/W2469952266","https://openalex.org/W2474909202","https://openalex.org/W2591957553","https://openalex.org/W2605350416","https://openalex.org/W2625746539","https://openalex.org/W2626454364","https://openalex.org/W2725606191","https://openalex.org/W2734755249","https://openalex.org/W2741249238","https://openalex.org/W2750004028","https://openalex.org/W2783272285","https://openalex.org/W2783944588","https://openalex.org/W2798385737","https://openalex.org/W2802187397","https://openalex.org/W2808310571","https://openalex.org/W2809307135","https://openalex.org/W2899457523","https://openalex.org/W2902040508","https://openalex.org/W2912213068","https://openalex.org/W2924612058","https://openalex.org/W2945623882","https://openalex.org/W2951431594","https://openalex.org/W2951645301","https://openalex.org/W2963085847","https://openalex.org/W2963367478","https://openalex.org/W2963403868","https://openalex.org/W2964044287","https://openalex.org/W2964296635","https://openalex.org/W2964316331","https://openalex.org/W2964926209","https://openalex.org/W2984100107","https://openalex.org/W2986515219","https://openalex.org/W2990816204","https://openalex.org/W2997261254","https://openalex.org/W2997329666","https://openalex.org/W3098231197","https://openalex.org/W3101157305","https://openalex.org/W3101201690","https://openalex.org/W3101707147","https://openalex.org/W3102619277"],"related_works":["https://openalex.org/W2374250903","https://openalex.org/W4386781444","https://openalex.org/W3092950680","https://openalex.org/W2150182025","https://openalex.org/W4246980185","https://openalex.org/W4317039510","https://openalex.org/W3197542405","https://openalex.org/W4360604087","https://openalex.org/W3206937279","https://openalex.org/W4310074695"],"abstract_inverted_index":{"Sequential":[0],"recommendation":[1,129,166],"has":[2],"been":[3],"a":[4,144,190,204,233],"hot":[5],"research":[6],"topic":[7],"because":[8],"of":[9,42,88,100,121,134,199,218,249,275,301],"its":[10],"practicability":[11],"and":[12,33,45,57,131,142,187,203,211,271],"high":[13],"accuracy":[14],"by":[15,78,97,138,214,259],"capturing":[16],"the":[17,31,40,80,85,98,101,118,132,139,162,170,177,197,209,216,219,245,250,257,261,264,267,272],"sequential":[18,128,157,165],"information.":[19],"As":[20],"deep":[21],"learning":[22,173,193,227],"(DL)":[23],"based":[24],"methods":[25,67,130],"being":[26],"widely":[27],"adopted":[28],"to":[29,49,104,175,195,240],"model":[30,168],"local":[32,171,210],"dynamic":[34,178],"preferences":[35,47,124,179,202],"beneath":[36,180],"users\u2019":[37,43,59,72,89,122,135,181,200],"behavior":[38,182],"sequences,":[39],"modeling":[41,120,198,260],"global":[44,123,191,201,212,225,273],"static":[46],"tends":[48],"be":[50,75,95,105,230],"underestimated":[51],"that":[52,71,207,291],"usually,":[53],"only":[54],"some":[55],"simple":[56],"crude":[58],"latent":[60],"representations":[61,213],"are":[62],"introduced.":[63],"Moreover,":[64],"most":[65,126],"existing":[66],"hold":[68],"an":[69,279],"assumption":[70],"intention":[73,90,136],"can":[74,229],"fully":[76],"captured":[77],"considering":[79],"historical":[81],"behaviors,":[82],"while":[83],"neglect":[84],"possible":[86],"uncertainty":[87,133],"in":[91,125,184,242,299],"reality,":[92],"which":[93,237],"may":[94],"influenced":[96],"appearance":[99],"candidate":[102,140,220,265],"items":[103,221],"recommended.":[106],"In":[107],"this":[108],"paper,":[109],"we":[110,160],"thus":[111],"focus":[112],"on":[113,285],"these":[114],"two":[115,302],"issues,":[116],"i.e.,":[117],"imperfect":[119],"DL-based":[127],"brought":[137],"items,":[141],"propose":[143,189],"novel":[145],"solution":[146],"named":[147],"fusing":[148],"item":[149,270],"similarity":[150],"models":[151],"with":[152,244],"self-attention":[153,251],"networks":[154],"(FISSA)":[155],"for":[156],"recommendation.":[158],"Specifically,":[159],"treat":[161],"state-of-the-art":[163,297],"self-attentive":[164],"(SASRec)":[167],"as":[169,232],"representation":[172,192,226],"module":[174,194,206,228,255],"capture":[176],"sequences":[183],"our":[185,292],"FISSA,":[186],"further":[188],"improve":[196],"gating":[205,254],"balances":[208],"taking":[215],"information":[217],"into":[222],"account.":[223],"The":[224,253],"seen":[231],"location-based":[234],"attention":[235],"layer,":[236],"is":[238],"effective":[239],"fit":[241],"well":[243],"parallelization":[246],"training":[247],"process":[248],"framework.":[252],"calculates":[256],"weight":[258],"relationship":[262],"among":[263],"item,":[266],"recently":[268],"interacted":[269],"preference":[274],"each":[276],"user":[277],"using":[278],"MLP":[280],"layer.":[281],"Extensive":[282],"empirical":[283],"studies":[284],"five":[286],"commonly":[287,303],"used":[288,304],"datasets":[289],"show":[290],"FISSA":[293],"significantly":[294],"outperforms":[295],"eight":[296],"baselines":[298],"terms":[300],"metrics.":[305]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":8}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}