{"id":"https://openalex.org/W4281256372","doi":"https://doi.org/10.1145/3534678.3539083","title":"AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System","display_name":"AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4281256372","doi":"https://doi.org/10.1145/3534678.3539083"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539083","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539083","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and 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/A5100674503","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0001-9764-1290"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xiang Li","raw_affiliation_strings":["Meituan Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100305955","display_name":"Xiaojiang Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaojiang Zhou","raw_affiliation_strings":["Meituan Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701345","display_name":"Yao Xiao","orcid":"https://orcid.org/0000-0002-9438-7431"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao Xiao","raw_affiliation_strings":["Meituan Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048448098","display_name":"Peihao Huang","orcid":"https://orcid.org/0000-0002-9835-6667"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peihao Huang","raw_affiliation_strings":["Meituan Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088945883","display_name":"Dayao Chen","orcid":"https://orcid.org/0009-0005-4500-1044"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dayao Chen","raw_affiliation_strings":["Meituan Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan Inc., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100320969","display_name":"Sheng Chen","orcid":"https://orcid.org/0000-0001-6882-600X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sheng Chen","raw_affiliation_strings":["Meituan Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan Inc., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086726545","display_name":"Yunsen Xian","orcid":"https://orcid.org/0000-0002-5303-9641"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yunsen Xian","raw_affiliation_strings":["Meituan Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Meituan Inc., Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100674503"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2397,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.56245544,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3241","last_page":"3249"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9977999925613403,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/ranking-svm","display_name":"Ranking SVM","score":0.8527700901031494},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.8486276865005493},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7685176134109497},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5590789318084717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5157454609870911},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5053120255470276},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.43266937136650085},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4316653907299042},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.42117840051651},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32498642802238464},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09952327609062195}],"concepts":[{"id":"https://openalex.org/C124975894","wikidata":"https://www.wikidata.org/wiki/Q7293290","display_name":"Ranking SVM","level":3,"score":0.8527700901031494},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.8486276865005493},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7685176134109497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5590789318084717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5157454609870911},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5053120255470276},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.43266937136650085},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4316653907299042},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.42117840051651},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32498642802238464},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09952327609062195},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3534678.3539083","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539083","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2136189984","https://openalex.org/W2194775991","https://openalex.org/W2512971201","https://openalex.org/W2723293840","https://openalex.org/W2783666221","https://openalex.org/W2808847742","https://openalex.org/W2913059114","https://openalex.org/W2963420686","https://openalex.org/W2963601856","https://openalex.org/W2964182926","https://openalex.org/W3034406766","https://openalex.org/W3034764953","https://openalex.org/W3041360407","https://openalex.org/W3080249509","https://openalex.org/W3081190557","https://openalex.org/W3081362488","https://openalex.org/W3093907268","https://openalex.org/W3104506006","https://openalex.org/W3106181667","https://openalex.org/W3155298021","https://openalex.org/W3208642157","https://openalex.org/W4213052788"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W2138488530","https://openalex.org/W4385565564","https://openalex.org/W2031468273","https://openalex.org/W2370100764","https://openalex.org/W2387658907","https://openalex.org/W2351112195","https://openalex.org/W4378464883","https://openalex.org/W2898073868","https://openalex.org/W2110822809"],"abstract_inverted_index":{"Industrial":[0],"search":[1,181,209],"and":[2,16,122,140],"recommendation":[3],"systems":[4],"mostly":[5],"follow":[6],"the":[7,32,39,66,72,77,87,103,120,125,131,136,162,187,204,208],"classic":[8],"multi-stage":[9],"information":[10],"retrieval":[11],"paradigm:":[12],"matching,":[13],"pre-ranking,":[14],"ranking,":[15],"re-ranking":[17],"stages.":[18],"To":[19],"account":[20],"for":[21,50,130,166],"system":[22,59,182,210],"efficiency,":[23],"simple":[24],"vector-product":[25],"based":[26],"models":[27,45,49],"are":[28],"commonly":[29],"deployed":[30],"in":[31,57,76,177,203,207],"pre-ranking":[33,48,58,78,93,126,164,205],"stage.":[34],"Recent":[35],"works":[36],"consider":[37],"distilling":[38],"high":[40],"knowledge":[41,90],"of":[42,105,124,211],"large":[43],"ranking":[44,88,152,169],"to":[46,82,91],"small":[47],"better":[51],"effectiveness.":[52],"However,":[53],"two":[54],"major":[55],"challenges":[56],"still":[60,100],"exist:":[61],"(i)":[62,128],"without":[63,171],"explicitly":[64],"modeling":[65],"performance":[67],"gain":[68],"versus":[69],"computation":[70,173],"cost,":[71],"predefined":[73],"latency":[74],"constraint":[75],"stage":[79],"inevitably":[80],"leads":[81],"suboptimal":[83],"solutions;":[84],"(ii)":[85,149],"transferring":[86],"teacher's":[89],"a":[92,96,111,167,193],"student":[94],"with":[95,151],"predetermined":[97],"handcrafted":[98],"architecture":[99,165],"suffers":[101],"from":[102],"loss":[104],"model":[106,153,199],"performance.":[107],"In":[108],"this":[109],"work,":[110],"novel":[112],"framework":[113],"AutoFAS":[114,129,159,184],"is":[115],"proposed":[116],"which":[117],"jointly":[118],"optimizes":[119],"efficiency":[121],"effectiveness":[123],"model:":[127],"first":[132],"time":[133],"simultaneously":[134],"selects":[135],"most":[137],"valuable":[138],"features":[139],"network":[141],"architectures":[142],"using":[143],"Neural":[144],"Architecture":[145],"Search":[146],"(NAS)":[147],"technique;":[148],"equipped":[150],"guided":[154],"reward":[155],"during":[156],"NAS":[157],"procedure,":[158],"can":[160],"select":[161],"best":[163],"given":[168],"teacher":[170],"any":[172],"overhead.":[174],"Experimental":[175],"results":[176],"our":[178,198],"real":[179],"world":[180],"show":[183],"consistently":[185],"outperforms":[186],"previous":[188],"state-of-the-art":[189],"(SOTA)":[190],"approaches":[191],"at":[192],"lower":[194],"computing":[195],"cost.":[196],"Notably,":[197],"has":[200],"been":[201],"adopted":[202],"module":[206],"Meituan,":[212],"bringing":[213],"significant":[214],"improvements.":[215]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}