{"id":"https://openalex.org/W3208809827","doi":"https://doi.org/10.1145/3459637.3481910","title":"Dual Learning for Query Generation and Query Selection in Query Feeds Recommendation","display_name":"Dual Learning for Query Generation and Query Selection in Query Feeds Recommendation","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3208809827","doi":"https://doi.org/10.1145/3459637.3481910","mag":"3208809827"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3481910","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3481910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5035508330","display_name":"Kunxun Qi","orcid":"https://orcid.org/0000-0002-2356-4103"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kunxun Qi","raw_affiliation_strings":["Sun Yat-sen University&amp;Tencent, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University&amp;Tencent, Guangzhou, China","institution_ids":["https://openalex.org/I157773358","https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086280314","display_name":"Ruoxu Wang","orcid":"https://orcid.org/0000-0002-7088-5954"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruoxu Wang","raw_affiliation_strings":["Tencent, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063038804","display_name":"Qikai Lu","orcid":"https://orcid.org/0000-0002-9879-3648"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Qikai Lu","raw_affiliation_strings":["University of Alberta, Edmonton, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100617079","display_name":"Xuejiao Wang","orcid":"https://orcid.org/0000-0001-5326-7524"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuejiao Wang","raw_affiliation_strings":["Tencent, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087324251","display_name":"Ning Jing","orcid":"https://orcid.org/0000-0002-4144-4658"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Jing","raw_affiliation_strings":["Tencent, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032424832","display_name":"Di Niu","orcid":"https://orcid.org/0000-0002-5250-7327"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Di Niu","raw_affiliation_strings":["University of Alberta, Edmonton, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062624991","display_name":"Haolan Chen","orcid":"https://orcid.org/0009-0004-8226-9608"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haolan Chen","raw_affiliation_strings":["Tencent, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.293,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54265734,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4065","last_page":"4074"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9984999895095825,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9984999895095825,"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":0.9016653299331665},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6595582962036133},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6380163431167603},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.59588623046875},{"id":"https://openalex.org/keywords/web-query-classification","display_name":"Web query classification","score":0.5573300719261169},{"id":"https://openalex.org/keywords/readability","display_name":"Readability","score":0.553132176399231},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5064398050308228},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.4675440192222595},{"id":"https://openalex.org/keywords/web-search-query","display_name":"Web search query","score":0.45377853512763977},{"id":"https://openalex.org/keywords/sargable","display_name":"Sargable","score":0.42537933588027954},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.4183051586151123},{"id":"https://openalex.org/keywords/query-language","display_name":"Query language","score":0.41155076026916504},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3662490248680115},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.3572297990322113},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21076330542564392}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9016653299331665},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6595582962036133},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6380163431167603},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.59588623046875},{"id":"https://openalex.org/C118689300","wikidata":"https://www.wikidata.org/wiki/Q7978614","display_name":"Web query classification","level":4,"score":0.5573300719261169},{"id":"https://openalex.org/C2778143727","wikidata":"https://www.wikidata.org/wiki/Q1820650","display_name":"Readability","level":2,"score":0.553132176399231},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5064398050308228},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.4675440192222595},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.45377853512763977},{"id":"https://openalex.org/C192939062","wikidata":"https://www.wikidata.org/wiki/Q104840822","display_name":"Sargable","level":4,"score":0.42537933588027954},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.4183051586151123},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.41155076026916504},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3662490248680115},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.3572297990322113},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21076330542564392},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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:10.1145/3459637.3481910","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3481910","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1784711535","display_name":null,"funder_award_id":"61976232,61876204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1840435438","https://openalex.org/W1979459060","https://openalex.org/W1981131819","https://openalex.org/W2064675550","https://openalex.org/W2083222330","https://openalex.org/W2086751477","https://openalex.org/W2101105183","https://openalex.org/W2104120831","https://openalex.org/W2111316763","https://openalex.org/W2121759027","https://openalex.org/W2130942839","https://openalex.org/W2135843591","https://openalex.org/W2155027007","https://openalex.org/W2257979135","https://openalex.org/W2546938941","https://openalex.org/W2551396370","https://openalex.org/W2602856279","https://openalex.org/W2606974598","https://openalex.org/W2895953440","https://openalex.org/W2913668833","https://openalex.org/W2914971589","https://openalex.org/W2946532448","https://openalex.org/W2952709651","https://openalex.org/W2962939608","https://openalex.org/W2963250244","https://openalex.org/W2963341956","https://openalex.org/W2963371447","https://openalex.org/W2963403868","https://openalex.org/W2963774520","https://openalex.org/W2963846996","https://openalex.org/W2964121744","https://openalex.org/W2965052260","https://openalex.org/W2981852735","https://openalex.org/W2998056485","https://openalex.org/W3034242983","https://openalex.org/W3034608141","https://openalex.org/W3034961030","https://openalex.org/W3035050380","https://openalex.org/W3035647909","https://openalex.org/W3081232010","https://openalex.org/W3099872554","https://openalex.org/W3100195825","https://openalex.org/W3115487106","https://openalex.org/W4231856373","https://openalex.org/W4237040408","https://openalex.org/W4288089799"],"related_works":["https://openalex.org/W2096359267","https://openalex.org/W2572349046","https://openalex.org/W2026738364","https://openalex.org/W2124814993","https://openalex.org/W2392799717","https://openalex.org/W2017989738","https://openalex.org/W3125756434","https://openalex.org/W2113390685","https://openalex.org/W1981131819","https://openalex.org/W2146885082"],"abstract_inverted_index":{"Query":[0],"feeds":[1,74],"recommendation":[2,75],"is":[3,38,88,92],"a":[4,13,27,43,104,145,166,190],"new":[5],"recommended":[6,20],"paradigm":[7],"in":[8,49,90],"mobile":[9],"search":[10,51],"applications,":[11],"where":[12],"stream":[14],"of":[15,30,45,63,115,185,198,211],"queries":[16,32,41,47,55,82,111,131,152],"need":[17],"to":[18,21,39,78,94,108,129,149,157,171],"be":[19,158],"improve":[22,135],"user":[23,50],"engagement.":[24],"It":[25],"requires":[26],"great":[28],"quantity":[29],"attractive":[31],"for":[33,71,83],"recommendation.":[34],"A":[35],"conventional":[36],"solution":[37],"retrieve":[40],"from":[42,132,202],"collection":[44],"past":[46],"recorded":[48],"logs.":[52],"However,":[53],"these":[54],"usually":[56],"have":[57],"poor":[58],"readability":[59],"and":[60,66,124,177,205],"limited":[61],"coverage":[62],"article":[64],"content,":[65],"are":[67,154],"thus":[68],"not":[69],"suitable":[70],"the":[72,80,113,136,151,174,178,186,196,209],"query":[73,105],"scenario.":[76],"Furthermore,":[77],"deploy":[79],"generated":[81],"recommendation,":[84],"human":[85,140,161],"validation,":[86,141],"which":[87],"costly":[89],"practice,":[91],"required":[93],"filter":[95],"unsuitable":[96],"queries.":[97],"In":[98],"this":[99],"paper,":[100],"we":[101,142,164],"propose":[102,144,165],"TitIE,":[103],"mining":[106],"system":[107],"generate":[109,130],"valuable":[110],"using":[112],"titles":[114],"documents.":[116],"We":[117],"employ":[118],"both":[119,199,203],"an":[120,125],"extractive":[121],"text":[122,127],"generator":[123,128],"abstractive":[126],"titles.":[133],"To":[134],"acceptance":[137],"rate":[138],"during":[139,160],"further":[143],"model-based":[146],"scoring":[147],"strategy":[148],"pre-select":[150],"that":[153],"more":[155],"likely":[156],"accepted":[159],"validation.":[162],"Finally,":[163],"novel":[167],"dual":[168],"learning":[169],"approach":[170],"jointly":[172],"learn":[173],"generation":[175],"model":[176,180],"selection":[179],"by":[181],"making":[182],"full":[183],"use":[184],"unlabeled":[187],"corpora":[188],"under":[189],"semi-supervised":[191],"scheme,":[192],"thereby":[193],"simultaneously":[194],"improving":[195],"performance":[197],"models.":[200],"Results":[201],"offline":[204],"online":[206],"evaluations":[207],"demonstrate":[208],"superiority":[210],"our":[212],"approach.":[213]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
