{"id":"https://openalex.org/W2911277147","doi":"https://doi.org/10.1145/3289600.3291375","title":"DAPA","display_name":"DAPA","publication_year":2019,"publication_date":"2019-01-30","ids":{"openalex":"https://openalex.org/W2911277147","doi":"https://doi.org/10.1145/3289600.3291375","mag":"2911277147"},"language":"en","primary_location":{"id":"doi:10.1145/3289600.3291375","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3289600.3291375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","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/A5006971161","display_name":"Yixing Fan","orcid":"https://orcid.org/0000-0003-4317-2702"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixing Fan","raw_affiliation_strings":["Institute of Computing Technology, CAS, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089655391","display_name":"Qingyao Ai","orcid":"https://orcid.org/0000-0002-5030-709X"},"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":"Qingyao Ai","raw_affiliation_strings":["University of Massachusetts Amherst, Massachusetts, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Massachusetts, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384130","display_name":"Zhaochun Ren","orcid":"https://orcid.org/0000-0002-9076-6565"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaochun Ren","raw_affiliation_strings":["JD.com, beijing, AK, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD.com, beijing, AK, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111614684","display_name":"Liangjie Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I21160419","display_name":"Ansys (United States)","ror":"https://ror.org/05cf5b117","country_code":"US","type":"company","lineage":["https://openalex.org/I21160419"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liangjie Hong","raw_affiliation_strings":["Etsy Inc., New York City, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Etsy Inc., New York City, NY, USA","institution_ids":["https://openalex.org/I21160419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054482111","display_name":"Dawei Yin","orcid":"https://orcid.org/0000-0002-8846-2001"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawei Yin","raw_affiliation_strings":["JD.com, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD.com, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088621320","display_name":"Jiafeng Guo","orcid":"https://orcid.org/0000-0002-9509-8674"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiafeng Guo","raw_affiliation_strings":["Institute of Computing Technology, CAS, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2187,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.48412538,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"844","last_page":"845"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9965999722480774,"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":0.9902999997138977,"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":0.8082590103149414},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7765136957168579},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.7033648490905762},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6148694753646851},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5995908975601196},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.46575242280960083},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3844676911830902},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3582134246826172},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33806324005126953}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8082590103149414},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7765136957168579},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.7033648490905762},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6148694753646851},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5995908975601196},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.46575242280960083},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3844676911830902},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3582134246826172},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33806324005126953},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3289600.3291375","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3289600.3291375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2136189984","https://openalex.org/W2536015822","https://openalex.org/W2539671052","https://openalex.org/W2806617520"],"related_works":["https://openalex.org/W2384605597","https://openalex.org/W2387743295","https://openalex.org/W2115758952","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W2366230879","https://openalex.org/W3208425359","https://openalex.org/W2349927912","https://openalex.org/W3159777597","https://openalex.org/W4380075502"],"abstract_inverted_index":{"Matching":[0],"between":[1],"two":[2],"information":[3,11],"objects":[4],"is":[5],"the":[6,46,69,77,112,125,143],"core":[7],"of":[8,42,63,114,127,146],"many":[9,93],"different":[10,73,147],"retrieval":[12],"(IR)":[13],"applications":[14],"including":[15],"Web":[16],"search,":[17],"question":[18],"answering,":[19],"and":[20,35,56],"recommendation.":[21],"Recently,":[22],"deep":[23,49,64,80,115,129],"learning":[24,50],"methods":[25],"have":[26,58,83],"yielded":[27],"immense":[28],"success":[29],"in":[30,87,150],"speech":[31],"recognition,":[32],"computer":[33],"vision,":[34],"natural":[36],"language":[37],"processing,":[38],"significantly":[39],"advancing":[40],"state-of-the-art":[41],"these":[43,88,100],"areas.":[44],"In":[45,106],"IR":[47,74,104],"community,":[48],"has":[51],"also":[52],"attracted":[53],"much":[54],"attention,":[55],"researchers":[57],"proposed":[59],"a":[60],"large":[61],"number":[62],"matching":[65,70,81,116,130,148],"models":[66,82,101,117,131],"to":[67,95,102,118,123,132,138],"tackle":[68],"problem":[71],"for":[72],"applications.":[75,120],"Despite":[76],"fact":[78],"that":[79],"gained":[84],"significant":[85],"progress":[86],"areas,":[89],"there":[90],"are":[91],"still":[92],"challenges":[94],"be":[96],"addressed":[97],"when":[98],"applying":[99,128],"real":[103],"scenarios.":[105],"this":[107],"workshop,":[108],"we":[109],"focus":[110],"on":[111,142],"applicability":[113],"practical":[119],"We":[121],"aim":[122],"discuss":[124],"issues":[126],"production":[133],"systems,":[134],"as":[135,137],"well":[136],"shed":[139],"some":[140],"light":[141],"fundamental":[144],"characteristics":[145],"tasks":[149],"IR.":[151],"website":[152],":":[153],"https://wsdm2019-dapa.github.io/index.html":[154]},"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2019-02-21T00:00:00"}
