{"id":"https://openalex.org/W4384642587","doi":"https://doi.org/10.1145/3539618.3591999","title":"HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer","display_name":"HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4384642587","doi":"https://doi.org/10.1145/3539618.3591999"},"language":"en","primary_location":{"id":"doi:10.1145/3539618.3591999","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539618.3591999","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","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/A5044455276","display_name":"Kaize Ding","orcid":"https://orcid.org/0000-0001-6684-6752"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kaize Ding","raw_affiliation_strings":["Google, Tempe, USA"],"affiliations":[{"raw_affiliation_string":"Google, Tempe, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058812697","display_name":"Albert Jiongqian Liang","orcid":"https://orcid.org/0000-0003-3794-5393"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Albert Jiongqian Liang","raw_affiliation_strings":["Google, Mountain View, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005058150","display_name":"Bryan Perozzi","orcid":"https://orcid.org/0009-0002-1639-2056"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bryan Perozzi","raw_affiliation_strings":["Google, Mountain View, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092491115","display_name":"Ting Chen","orcid":"https://orcid.org/0009-0003-0645-7546"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ting Chen","raw_affiliation_strings":["Google, Mountain View, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000700211","display_name":"Ruoxi Wang","orcid":"https://orcid.org/0009-0002-4824-1316"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruoxi Wang","raw_affiliation_strings":["Google, Mountain View, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079085366","display_name":"Lichan Hong","orcid":"https://orcid.org/0009-0004-9563-554X"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lichan Hong","raw_affiliation_strings":["Google, Mountain View, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028125399","display_name":"Ed H.","orcid":"https://orcid.org/0000-0003-3230-5338"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ed H. Chi","raw_affiliation_strings":["Google, Mountain View, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100338946","display_name":"Huan Liu","orcid":"https://orcid.org/0000-0002-3264-7904"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huan Liu","raw_affiliation_strings":["Google, Tempe, USA"],"affiliations":[{"raw_affiliation_string":"Google, Tempe, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055484401","display_name":"Derek Zhiyuan Cheng","orcid":"https://orcid.org/0009-0000-7943-8328"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Derek Zhiyuan Cheng","raw_affiliation_strings":["Google, Mountain View, USA"],"affiliations":[{"raw_affiliation_string":"Google, Mountain View, USA","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5044455276"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":4.1098,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.94515699,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2062","last_page":"2066"},"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":0.9995999932289124,"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/T10028","display_name":"Topic Modeling","score":0.9987999796867371,"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/feature-learning","display_name":"Feature learning","score":0.7628774046897888},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6882462501525879},{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.627436637878418},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5736156702041626},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5431626439094543},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5352303385734558},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5064200162887573},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4514155387878418},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44814983010292053},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4437040090560913},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34161168336868286},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17841240763664246}],"concepts":[{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.7628774046897888},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6882462501525879},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.627436637878418},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5736156702041626},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5431626439094543},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5352303385734558},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5064200162887573},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4514155387878418},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44814983010292053},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4437040090560913},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34161168336868286},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17841240763664246},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3539618.3591999","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539618.3591999","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G5429966900","display_name":null,"funder_award_id":"2229461","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2027731328","https://openalex.org/W2155912844","https://openalex.org/W2295739661","https://openalex.org/W2475334473","https://openalex.org/W2509235963","https://openalex.org/W2517540742","https://openalex.org/W2723293840","https://openalex.org/W2793768763","https://openalex.org/W2892880750","https://openalex.org/W2898085636","https://openalex.org/W2911760887","https://openalex.org/W2964182926","https://openalex.org/W2979450518","https://openalex.org/W3035666843","https://openalex.org/W3096831136","https://openalex.org/W3098024612","https://openalex.org/W3101704389","https://openalex.org/W3104030692","https://openalex.org/W3104439459","https://openalex.org/W3106229813","https://openalex.org/W3153940464","https://openalex.org/W3154807520","https://openalex.org/W3167730891","https://openalex.org/W3198457408","https://openalex.org/W4225657277","https://openalex.org/W4281842213","https://openalex.org/W4382239158"],"related_works":["https://openalex.org/W4376608589","https://openalex.org/W1537073411","https://openalex.org/W3138003926","https://openalex.org/W1630514295","https://openalex.org/W4300037846","https://openalex.org/W4288275998","https://openalex.org/W2963081352","https://openalex.org/W4376608938","https://openalex.org/W2472555608","https://openalex.org/W4285218279"],"abstract_inverted_index":{"Learning":[0],"expressive":[1],"representations":[2,143],"for":[3],"high-dimensional":[4],"yet":[5],"sparse":[6,33,67,105,172],"features":[7,68,106],"has":[8],"been":[9],"a":[10,95,116,123],"longstanding":[11],"problem":[12,87],"in":[13,43,81],"information":[14],"retrieval.":[15],"Though":[16],"recent":[17],"deep":[18],"learning":[19,65,90,97,170],"methods":[20,50],"can":[21,165],"partially":[22],"solve":[23],"the":[24,31,44,54,63,86,104,131,140,147,154,162],"problem,":[25],"they":[26],"often":[27],"fail":[28],"to":[29,59,102],"handle":[30],"numerous":[32],"features,":[34],"particularly":[35],"those":[36],"tail":[37],"feature":[38,125,142,168],"values":[39],"with":[40],"infrequent":[41],"occurrences":[42],"training":[45],"data.":[46],"Worse":[47],"still,":[48],"existing":[49],"cannot":[51],"explicitly":[52],"leverage":[53],"correlations":[55,148,155],"among":[56,149,156],"different":[57,108,150],"instances":[58,109,151],"help":[60],"further":[61],"improve":[62,167],"representation":[64,89,169],"on":[66,91,130,135,171],"since":[69],"such":[70],"relational":[71],"prior":[72],"knowledge":[73],"is":[74],"not":[75,145],"provided.":[76],"To":[77],"address":[78],"these":[79],"challenges,":[80],"this":[82],"paper,":[83],"we":[84,100],"tackle":[85],"of":[88,107],"feature-sparse":[92],"data":[93,117],"from":[94],"graph":[96],"perspective.":[98],"Specifically,":[99],"propose":[101],"model":[103],"using":[110],"hypergraphs":[111,133],"where":[112],"each":[113,120],"node":[114],"represents":[115],"instance":[118],"and":[119],"hyperedge":[121],"denotes":[122],"distinct":[124],"value.":[126],"By":[127],"passing":[128],"messages":[129],"constructed":[132],"based":[134],"our":[136],"Hypergraph":[137],"Transformer":[138],"(HyperFormer),":[139],"learned":[141],"capture":[144],"only":[146],"but":[152],"also":[153],"features.":[157,173],"Our":[158],"experiments":[159],"demonstrate":[160],"that":[161],"proposed":[163],"approach":[164],"effectively":[166]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}