{"id":"https://openalex.org/W3170163874","doi":"https://doi.org/10.1145/3447548.3467216","title":"Retrieval & Interaction Machine for Tabular Data Prediction","display_name":"Retrieval & Interaction Machine for Tabular Data Prediction","publication_year":2021,"publication_date":"2021-08-12","ids":{"openalex":"https://openalex.org/W3170163874","doi":"https://doi.org/10.1145/3447548.3467216","mag":"3170163874"},"language":"en","primary_location":{"id":"doi:10.1145/3447548.3467216","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","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/A5060200431","display_name":"Jiarui Qin","orcid":"https://orcid.org/0000-0002-9064-885X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiarui Qin","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090720315","display_name":"Weinan Zhang","orcid":"https://orcid.org/0000-0002-0127-2425"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weinan Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101582349","display_name":"Rong Su","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Su","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100337382","display_name":"Zhirong Liu","orcid":"https://orcid.org/0000-0003-3358-0753"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhirong Liu","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101500385","display_name":"Weiwen Liu","orcid":"https://orcid.org/0000-0002-9148-3997"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwen Liu","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054330014","display_name":"Ruiming Tang","orcid":"https://orcid.org/0000-0002-9224-2431"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiming Tang","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083350101","display_name":"Xiuqiang He","orcid":"https://orcid.org/0000-0002-4115-8205"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuqiang He","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001571390","display_name":"Yong Yu","orcid":"https://orcid.org/0000-0003-0281-8271"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Yu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5060200431"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":5.9497,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.96256656,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1379","last_page":"1389"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.998199999332428,"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":0.998199999332428,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9973999857902527,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9955000281333923,"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":0.8047945499420166},{"id":"https://openalex.org/keywords/column","display_name":"Column (typography)","score":0.7754553556442261},{"id":"https://openalex.org/keywords/row","display_name":"Row","score":0.7171177268028259},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7113338112831116},{"id":"https://openalex.org/keywords/row-and-column-spaces","display_name":"Row and column spaces","score":0.5964478254318237},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5556483268737793},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5173580050468445},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5086356401443481},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4977865219116211},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49560534954071045},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.48472902178764343},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4574874937534332},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4389272928237915},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4311811327934265},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.4256933629512787},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36109232902526855},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3294631540775299},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.14135465025901794}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8047945499420166},{"id":"https://openalex.org/C2780551164","wikidata":"https://www.wikidata.org/wiki/Q2306599","display_name":"Column (typography)","level":3,"score":0.7754553556442261},{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.7171177268028259},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7113338112831116},{"id":"https://openalex.org/C104140500","wikidata":"https://www.wikidata.org/wiki/Q2088159","display_name":"Row and column spaces","level":3,"score":0.5964478254318237},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5556483268737793},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5173580050468445},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5086356401443481},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4977865219116211},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49560534954071045},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.48472902178764343},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4574874937534332},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4389272928237915},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4311811327934265},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.4256933629512787},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36109232902526855},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3294631540775299},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.14135465025901794},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447548.3467216","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447548.3467216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","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":36,"referenced_works":["https://openalex.org/W1482214997","https://openalex.org/W2143570267","https://openalex.org/W2171279286","https://openalex.org/W2295598076","https://openalex.org/W2295739661","https://openalex.org/W2443960221","https://openalex.org/W2467137869","https://openalex.org/W2475334473","https://openalex.org/W2509235963","https://openalex.org/W2517540742","https://openalex.org/W2548570154","https://openalex.org/W2604662567","https://openalex.org/W2605350416","https://openalex.org/W2723293840","https://openalex.org/W2734755249","https://openalex.org/W2740098507","https://openalex.org/W2783272285","https://openalex.org/W2788330850","https://openalex.org/W2793768763","https://openalex.org/W2911760887","https://openalex.org/W2942947041","https://openalex.org/W2945772520","https://openalex.org/W2962745591","https://openalex.org/W2963614749","https://openalex.org/W2963924287","https://openalex.org/W2964316331","https://openalex.org/W3035053861","https://openalex.org/W3081190557","https://openalex.org/W3093519337","https://openalex.org/W3098024612","https://openalex.org/W3100199015","https://openalex.org/W3102476541","https://openalex.org/W3104030692","https://openalex.org/W3105595718","https://openalex.org/W3106252282","https://openalex.org/W4289362008"],"related_works":["https://openalex.org/W3123744736","https://openalex.org/W3121299875","https://openalex.org/W1566754092","https://openalex.org/W1992086467","https://openalex.org/W2005695153","https://openalex.org/W2011918259","https://openalex.org/W2741429854","https://openalex.org/W4214886263","https://openalex.org/W3007479582","https://openalex.org/W1581345312"],"abstract_inverted_index":{"Prediction":[0],"over":[1,189],"tabular":[2,51,107],"data":[3,10,23,35,52],"is":[4,24],"an":[5],"essential":[6],"task":[7],"in":[8],"many":[9],"science":[11],"applications":[12],"such":[13],"as":[14,33,40,76,152],"recommender":[15],"systems,":[16],"online":[17],"advertising,":[18],"medical":[19],"treatment,":[20],"etc.":[21],"Tabular":[22],"structured":[25],"into":[26],"rows":[27,48,120,150],"and":[28,37,47,103,147,177,192,198],"columns,":[29],"with":[30,79],"each":[31,38],"row":[32,146],"a":[34,41,88],"sample":[36],"column":[39],"feature":[42,135],"attribute.":[43],"Both":[44],"the":[45,50,59,69,74,122,126,130,140,144,148,155,190,196],"columns":[46],"of":[49,121,129,166,200],"carry":[53],"useful":[54,119],"patterns":[55,71,105,142],"that":[56,98,184],"could":[57],"improve":[58],"model":[60],"prediction":[61,128,172,179],"performance.":[62],"However,":[63],"most":[64],"existing":[65],"models":[66],"focus":[67],"on":[68,163],"cross-column":[70,104,141],"yet":[72],"overlook":[73],"cross-rowpatterns":[75],"they":[77],"deal":[78],"single":[80],"samples":[81],"independently.":[82],"In":[83],"this":[84],"work,":[85],"we":[86],"propose":[87],"general":[89],"learning":[90],"framework":[91],"named":[92],"Retrieval":[93],"&":[94],"Interaction":[95],"Machine":[96],"(RIM)":[97],"fully":[99],"exploits":[100],"both":[101],"cross-row":[102],"among":[106,143],"data.":[108],"Specifically,":[109],"RIM":[110,185],"first":[111],"leverages":[112],"search":[113],"engine":[114],"techniques":[115],"to":[116,124,138,153],"efficiently":[117],"retrieve":[118],"table":[123],"assist":[125],"label":[127,157],"target":[131,145],"row,":[132],"then":[133],"uses":[134],"interaction":[136],"networks":[137],"capture":[139],"retrieved":[149],"so":[151],"make":[154],"final":[156],"prediction.":[158],"We":[159],"conduct":[160],"extensive":[161],"experiments":[162],"11":[164],"datasets":[165],"three":[167],"important":[168],"tasks,":[169],"i.e.,":[170],"CTR":[171],"(classification),":[173],"top-n":[174],"recommendation":[175],"(ranking)":[176],"rating":[178],"(regression).":[180],"Experimental":[181],"results":[182],"show":[183],"achieves":[186],"significant":[187],"improvements":[188],"state-of-the-art":[191],"various":[193],"baselines,":[194],"demonstrating":[195],"superiority":[197],"efficacy":[199],"RIM.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}