{"id":"https://openalex.org/W2510317721","doi":"https://doi.org/10.1145/2959100.2959180","title":"<i>Ask the GRU</i>","display_name":"<i>Ask the GRU</i>","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2510317721","doi":"https://doi.org/10.1145/2959100.2959180","mag":"2510317721"},"language":"en","primary_location":{"id":"doi:10.1145/2959100.2959180","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2959100.2959180","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2959180&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://dl.acm.org/ft_gateway.cfm?id=2959180&type=pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084271903","display_name":"Trapit Bansal","orcid":null},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Trapit Bansal","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, MA, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103250966","display_name":"David Belanger","orcid":"https://orcid.org/0000-0001-9673-1630"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Belanger","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, MA, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008354502","display_name":"Andrew McCallum","orcid":"https://orcid.org/0000-0003-2843-6992"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew McCallum","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, MA, USA"],"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084271903"],"corresponding_institution_ids":["https://openalex.org/I24603500"],"apc_list":null,"apc_paid":null,"fwci":74.5819,"has_fulltext":true,"cited_by_count":282,"citation_normalized_percentile":{"value":0.99926839,"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":"107","last_page":"114"},"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":0.9988999962806702,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9912999868392944,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.786357045173645},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.7136329412460327},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7102369070053101},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.5765663981437683},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5659714341163635},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5613535642623901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5540729761123657},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.49188780784606934},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4834771752357483},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.46089544892311096},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.45106935501098633},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.44500166177749634},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.441652774810791},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.43311935663223267},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4070514142513275},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3802697956562042},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2088642418384552}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.786357045173645},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.7136329412460327},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7102369070053101},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.5765663981437683},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5659714341163635},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5613535642623901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5540729761123657},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49188780784606934},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4834771752357483},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.46089544892311096},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.45106935501098633},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.44500166177749634},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.441652774810791},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.43311935663223267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4070514142513275},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3802697956562042},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2088642418384552},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2959100.2959180","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2959100.2959180","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2959180&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1609.02116","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1609.02116","pdf_url":"https://arxiv.org/pdf/1609.02116","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/2959100.2959180","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2959100.2959180","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2959180&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1667745721","display_name":"DMREF: Collaborative Research: The Synthesis Genome: Data Mining for Synthesis of New Materials","funder_award_id":"1534431","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2345705215","display_name":null,"funder_award_id":"DMR-1534431","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G414571346","display_name":null,"funder_award_id":"FA8750-13-2-0020","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G4713059963","display_name":null,"funder_award_id":"FA8750","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G5659604348","display_name":"CI-ADDO-EN: Flexible Machine Learning for Natural Language in the MALLET Toolkit","funder_award_id":"0958392","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320317052","display_name":"Allen Institute for Artificial Intelligence","ror":"https://ror.org/05w520734"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320337367","display_name":"Division of Materials Research","ror":"https://ror.org/01pc7k308"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2510317721.pdf","grobid_xml":"https://content.openalex.org/works/W2510317721.grobid-xml"},"referenced_works_count":68,"referenced_works":["https://openalex.org/W21006490","https://openalex.org/W179875071","https://openalex.org/W581956982","https://openalex.org/W1522301498","https://openalex.org/W1720514416","https://openalex.org/W1902674502","https://openalex.org/W1924770834","https://openalex.org/W1969245231","https://openalex.org/W2008886893","https://openalex.org/W2031237011","https://openalex.org/W2043403353","https://openalex.org/W2048657872","https://openalex.org/W2049633694","https://openalex.org/W2049965950","https://openalex.org/W2050096199","https://openalex.org/W2054141820","https://openalex.org/W2054553473","https://openalex.org/W2061212083","https://openalex.org/W2061873838","https://openalex.org/W2064675550","https://openalex.org/W2092694516","https://openalex.org/W2099866409","https://openalex.org/W2101409192","https://openalex.org/W2102982709","https://openalex.org/W2104210067","https://openalex.org/W2107878631","https://openalex.org/W2108153239","https://openalex.org/W2113552117","https://openalex.org/W2113858518","https://openalex.org/W2114079787","https://openalex.org/W2117420919","https://openalex.org/W2119825970","https://openalex.org/W2124029832","https://openalex.org/W2125261539","https://openalex.org/W2127480961","https://openalex.org/W2130942839","https://openalex.org/W2131774270","https://openalex.org/W2135790056","https://openalex.org/W2137028279","https://openalex.org/W2137245235","https://openalex.org/W2140310134","https://openalex.org/W2150355110","https://openalex.org/W2151451758","https://openalex.org/W2153579005","https://openalex.org/W2157331557","https://openalex.org/W2157881433","https://openalex.org/W2158515176","https://openalex.org/W2158899491","https://openalex.org/W2177562712","https://openalex.org/W2253995343","https://openalex.org/W2268318962","https://openalex.org/W2295739661","https://openalex.org/W2400777838","https://openalex.org/W2557283755","https://openalex.org/W2913340405","https://openalex.org/W2949888546","https://openalex.org/W2950133940","https://openalex.org/W2952230511","https://openalex.org/W2952729433","https://openalex.org/W2963655167","https://openalex.org/W2964159778","https://openalex.org/W2997617958","https://openalex.org/W3102701984","https://openalex.org/W4294170691","https://openalex.org/W6636133922","https://openalex.org/W6677019868","https://openalex.org/W6679436768","https://openalex.org/W6680451568"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2058118494","https://openalex.org/W2392768766","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W2382021449","https://openalex.org/W2095118173","https://openalex.org/W2103419012","https://openalex.org/W2106424170","https://openalex.org/W1985426483"],"abstract_inverted_index":{"In":[0,91,138],"a":[1,74,96,109,167],"variety":[2],"of":[3,85,127,147,169,185,187],"application":[4],"domains":[5],"the":[6,66,105,120,125,143,160,178,183,188],"content":[7,170],"to":[8,11,42,52,103],"be":[9,39],"recommended":[10],"users":[12],"is":[13,153,164],"associated":[14,23],"with":[15,22,134],"text.":[16],"This":[17,54,176],"includes":[18],"research":[19],"papers,":[20],"movies":[21],"plot":[24],"summaries,":[25],"news":[26],"articles,":[27],"blog":[28],"posts,":[29],"etc.":[30],"Recommendation":[31],"approaches":[32],"based":[33],"on":[34,119],"latent":[35,110],"factor":[36],"models":[37,82,133],"can":[38],"extended":[40],"naturally":[41],"leverage":[43],"text":[44,51,106,161],"by":[45,73,156],"employing":[46],"an":[47],"explicit":[48],"mapping":[49],"from":[50],"factors.":[53],"enables":[55],"recommendations":[56],"for":[57,68,88,166],"new,":[58],"unseen":[59],"content,":[60],"and":[61,172],"may":[62],"generalize":[63],"better,":[64],"since":[65],"factors":[67],"all":[69,146],"items":[70],"are":[71],"produced":[72],"compactly-parametrized":[75],"model.":[76],"Previous":[77],"work":[78],"has":[79],"used":[80],"topic":[81],"or":[83],"averages":[84],"word":[86,150],"embeddings":[87],"this":[89,92,131],"mapping.":[90],"paper":[93,129],"we":[94,141],"present":[95],"method":[97],"leveraging":[98],"deep":[99],"recurrent":[100,114],"neural":[101],"networks":[102],"encode":[104],"sequence":[107],"into":[108],"vector,":[111],"specifically":[112],"gated":[113],"units":[115],"(GRUs)":[116],"trained":[117,165],"end-to-end":[118],"collaborative":[121,179],"filtering":[122,180],"task.":[123],"For":[124],"task":[126],"scientific":[128],"recommendation,":[130],"yields":[132],"significantly":[135],"higher":[136],"accuracy.":[137],"cold-start":[139],"scenarios,":[140],"beat":[142],"previous":[144],"state-of-the-art,":[145],"which":[148],"ignore":[149],"order.":[151],"Performance":[152],"further":[154],"improved":[155],"multi-task":[157],"learning,":[158],"where":[159],"encoder":[162],"network":[163],"combination":[168],"recommendation":[171],"item":[173],"metadata":[174],"prediction.":[175],"regularizes":[177],"model,":[181],"ameliorating":[182],"problem":[184],"sparsity":[186],"observed":[189],"rating":[190],"matrix.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":49},{"year":2020,"cited_by_count":57},{"year":2019,"cited_by_count":50},{"year":2018,"cited_by_count":35},{"year":2017,"cited_by_count":22},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2016-09-16T00:00:00"}
