{"id":"https://openalex.org/W2746011824","doi":"https://doi.org/10.1145/3109859.3109872","title":"When Recurrent Neural Networks meet the Neighborhood for Session-Based Recommendation","display_name":"When Recurrent Neural Networks meet the Neighborhood for Session-Based Recommendation","publication_year":2017,"publication_date":"2017-08-24","ids":{"openalex":"https://openalex.org/W2746011824","doi":"https://doi.org/10.1145/3109859.3109872","mag":"2746011824"},"language":"en","primary_location":{"id":"doi:10.1145/3109859.3109872","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3109859.3109872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eleventh 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/A5005545405","display_name":"Dietmar Jannach","orcid":"https://orcid.org/0000-0002-4698-8507"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Dietmar Jannach","raw_affiliation_strings":["TU Dortmund, Dortmund, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Dortmund, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024478938","display_name":"Malte Ludewig","orcid":"https://orcid.org/0000-0001-9051-351X"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Malte Ludewig","raw_affiliation_strings":["TU Dortmund, Dortmund, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Dortmund, Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5005545405"],"corresponding_institution_ids":["https://openalex.org/I200332995"],"apc_list":null,"apc_paid":null,"fwci":87.016,"has_fulltext":false,"cited_by_count":494,"citation_normalized_percentile":{"value":0.99936652,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"306","last_page":"310"},"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/T10028","display_name":"Topic Modeling","score":0.9986000061035156,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8616217970848083},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.745855450630188},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.7458361387252808},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7219526767730713},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.653765082359314},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6240069270133972},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5927084684371948},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5788081288337708},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5731299519538879},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5687564015388489},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4590751826763153},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.436227023601532},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08599978685379028}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8616217970848083},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.745855450630188},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.7458361387252808},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7219526767730713},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.653765082359314},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6240069270133972},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5927084684371948},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5788081288337708},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5731299519538879},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5687564015388489},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4590751826763153},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.436227023601532},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08599978685379028},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3109859.3109872","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3109859.3109872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eleventh 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":44,"referenced_works":["https://openalex.org/W1810943226","https://openalex.org/W1838102683","https://openalex.org/W1924770834","https://openalex.org/W1978609982","https://openalex.org/W1987961977","https://openalex.org/W1989318262","https://openalex.org/W2000368573","https://openalex.org/W2017107296","https://openalex.org/W2027731328","https://openalex.org/W2027829212","https://openalex.org/W2038585576","https://openalex.org/W2042996020","https://openalex.org/W2064675550","https://openalex.org/W2110485445","https://openalex.org/W2114079787","https://openalex.org/W2114596616","https://openalex.org/W2117111450","https://openalex.org/W2138108551","https://openalex.org/W2157881433","https://openalex.org/W2171279286","https://openalex.org/W2241862190","https://openalex.org/W2337327449","https://openalex.org/W2394764681","https://openalex.org/W2462723856","https://openalex.org/W2469952266","https://openalex.org/W2471920251","https://openalex.org/W2474765392","https://openalex.org/W2474909202","https://openalex.org/W2487744644","https://openalex.org/W2500403796","https://openalex.org/W2510317721","https://openalex.org/W2512965516","https://openalex.org/W2512971201","https://openalex.org/W2513020047","https://openalex.org/W2515144511","https://openalex.org/W2528967048","https://openalex.org/W2618462075","https://openalex.org/W2964316331","https://openalex.org/W3099732023","https://openalex.org/W3102895136","https://openalex.org/W4293585414","https://openalex.org/W4300175872","https://openalex.org/W4300528642","https://openalex.org/W6630221451"],"related_works":["https://openalex.org/W2280422768","https://openalex.org/W3143197806","https://openalex.org/W4252555497","https://openalex.org/W4386781444","https://openalex.org/W3092950680","https://openalex.org/W2150182025","https://openalex.org/W4246980185","https://openalex.org/W3121175838","https://openalex.org/W3016293053","https://openalex.org/W4317039510"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"methods":[2],"have":[3],"led":[4],"to":[5,24],"substantial":[6],"progress":[7],"in":[8,15,45,78,99,128,155,177],"various":[9],"application":[10,54],"fields":[11],"of":[12,20,35,55,68,95,132,148],"AI,":[13],"and":[14,91,136,140],"recent":[16],"years":[17],"a":[18,113,118],"number":[19],"proposals":[21],"were":[22,158],"made":[23],"improve":[25],"recommender":[26],"systems":[27],"with":[28,59,167],"artificial":[29],"neural":[30,57],"networks.":[31],"For":[32],"the":[33,42,53,65,79,93,96,100,129,133,146,149,156,164,178,185],"problem":[34],"making":[36],"session-based":[37],"recommendations,":[38],"i.e.,":[39],"for":[40,124],"recommending":[41],"next":[43],"item":[44],"an":[46],"anonymous":[47],"session,":[48],"Hidasi":[49],"et":[50],"al.~recently":[51],"investigated":[52],"recurrent":[56],"networks":[58],"Gated":[60],"Recurrent":[61],"Units":[62],"(GRU4REC).":[63],"Assessing":[64],"true":[66],"effectiveness":[67],"such":[69],"novel":[70],"approaches":[71],"based":[72,111],"only":[73],"on":[74,112],"what":[75],"is":[76,81,103],"reported":[77],"literature":[80],"however":[82],"difficult":[83],"when":[84,92,161],"no":[85],"standard":[86],"evaluation":[87,116],"protocols":[88],"are":[89],"applied":[90],"strength":[94],"baselines":[97],"used":[98],"performance":[101],"comparison":[102],"not":[104],"clear.":[105],"In":[106],"this":[107],"work":[108],"we":[109,162],"show":[110],"comprehensive":[114],"empirical":[115],"that":[117,171,180],"heuristics-based":[119],"nearest":[120],"neighbor":[121],"(kNN)":[122],"scheme":[123],"sessions":[125],"outperforms":[126],"GRU4REC":[127],"large":[130],"majority":[131],"tested":[134],"configurations":[135],"datasets.":[137],"Neighborhood":[138],"sampling":[139],"efficient":[141],"in-memory":[142],"data":[143,179],"structures":[144],"ensure":[145],"scalability":[147],"kNN":[150,165,187],"method.":[151,188],"The":[152],"best":[153],"results":[154],"end":[157],"often":[159],"achieved":[160],"combine":[163],"approach":[166],"GRU4REC,":[168],"which":[169],"shows":[170],"RNNs":[172],"can":[173],"leverage":[174],"sequential":[175],"signals":[176],"cannot":[181],"be":[182],"detected":[183],"by":[184],"co-occurrence-based":[186]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":43},{"year":2024,"cited_by_count":72},{"year":2023,"cited_by_count":61},{"year":2022,"cited_by_count":70},{"year":2021,"cited_by_count":67},{"year":2020,"cited_by_count":68},{"year":2019,"cited_by_count":68},{"year":2018,"cited_by_count":31},{"year":2017,"cited_by_count":5},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-10-10T00:00:00"}