{"id":"https://openalex.org/W198554346","doi":"https://doi.org/10.1145/2567948.2577317","title":"Query augmentation based intent matching in retail vertical ads","display_name":"Query augmentation based intent matching in retail vertical ads","publication_year":2014,"publication_date":"2014-04-07","ids":{"openalex":"https://openalex.org/W198554346","doi":"https://doi.org/10.1145/2567948.2577317","mag":"198554346"},"language":"en","primary_location":{"id":"doi:10.1145/2567948.2577317","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2567948.2577317","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd International Conference on World Wide Web","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/A5046520437","display_name":"Huasha Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I134446601","display_name":"Berkeley College","ror":"https://ror.org/02xewxa75","country_code":"US","type":"education","lineage":["https://openalex.org/I134446601"]},{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Huasha Zhao","raw_affiliation_strings":["UC Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"UC Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103114370","display_name":"Vivian Zhang","orcid":"https://orcid.org/0000-0002-3282-5766"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vivian Zhang","raw_affiliation_strings":["Microsoft, Sunnyvale, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft, Sunnyvale, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359105","display_name":"Ye Chen","orcid":"https://orcid.org/0000-0002-4541-5918"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ye Chen","raw_affiliation_strings":["Microsoft, Sunnyvale, CA, USA","Microsoft, Sunnyvale, CA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft, Sunnyvale, CA, USA#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089723214","display_name":"John Canny","orcid":"https://orcid.org/0000-0002-7161-7927"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Canny","raw_affiliation_strings":["UC Berkeley, Sunnyvale, CA, USA","UC Berkeley, Sunnyvale, CA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"UC Berkeley, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"UC Berkeley, Sunnyvale, CA, USA#TAB#","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109035293","display_name":"Tak W. Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tak Yan","raw_affiliation_strings":["Microsoft, Sunnyvale, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft, Sunnyvale, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5046520437"],"corresponding_institution_ids":["https://openalex.org/I134446601","https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02702923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"419","last_page":"420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9991000294685364,"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":0.9991000294685364,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.998199999332428,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9976000189781189,"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":0.7389434576034546},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.7189192175865173},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6579235792160034},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6331090331077576},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4971669018268585},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.49612268805503845},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.4814671576023102},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4795110523700714},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.46424850821495056},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.44538652896881104},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12871438264846802},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11205646395683289}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7389434576034546},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.7189192175865173},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6579235792160034},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6331090331077576},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4971669018268585},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.49612268805503845},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.4814671576023102},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4795110523700714},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.46424850821495056},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.44538652896881104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12871438264846802},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11205646395683289},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2567948.2577317","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2567948.2577317","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd International Conference on World Wide Web","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2135500808","https://openalex.org/W2170741935"],"related_works":["https://openalex.org/W2085384747","https://openalex.org/W2088166309","https://openalex.org/W1891216533","https://openalex.org/W4312133475","https://openalex.org/W4238976562","https://openalex.org/W2276587472","https://openalex.org/W2615795876","https://openalex.org/W2358294942","https://openalex.org/W4367460280","https://openalex.org/W2156296249"],"abstract_inverted_index":{"Search":[0],"advertising":[1],"shows":[2],"trends":[3],"of":[4,13,21],"vertical":[5,30,163],"extension.":[6],"Vertical":[7],"ads":[8,31,48,70,83,88,134,139,164],"typically":[9],"offer":[10],"better":[11,22],"Return":[12],"Investment":[14],"(ROI)":[15],"to":[16,81,150,161],"advertisers":[17],"as":[18],"a":[19,40,68,93,105],"result":[20],"user":[23,45,101,152],"engagement.":[24],"However,":[25],"campaign":[26],"and":[27,47,53,125,158],"bids":[28],"in":[29,133,155],"are":[32,113],"not":[33],"set":[34],"at":[35],"the":[36,42,54,121,147,162],"keyword":[37],"level.":[38],"As":[39],"result,":[41],"matching":[43,97,157],"between":[44],"query":[46,75],"suffers":[49],"low":[50],"recall":[51,84],"rate":[52,136],"match":[55],"quality":[56],"is":[57,146],"heavily":[58],"impacted":[59],"by":[60],"tail":[61],"queries.":[62,110],"In":[63],"this":[64,144],"paper,":[65],"we":[66,90],"propose":[67],"retail":[69],"retrieval":[71,135],"framework":[72],"based":[73],"on":[74,108,116],"rewrite":[76],"using":[77],"personal":[78],"history":[79],"data":[80,154],"improve":[82],"rate.":[85],"To":[86,141],"insure":[87],"quality,":[89],"also":[91],"present":[92],"relevance":[94],"model":[95],"for":[96],"rewritten":[98],"queries":[99],"with":[100,104],"search":[102,123],"intent,":[103],"particular":[106],"focus":[107],"rare":[109],"Extensive":[111],"experiments":[112],"carried":[114],"out":[115],"large-scale":[117],"logs":[118],"collected":[119],"from":[120],"Bing":[122],"engine,":[124],"results":[126],"show":[127],"our":[128,142],"system":[129],"achieves":[130],"significant":[131],"gains":[132],"without":[137],"compromising":[138],"quality.":[140],"knowledge,":[143],"work":[145],"first":[148],"attempt":[149],"leverage":[151],"behavioral":[153],"ad":[156],"apply":[159],"it":[160],"domain.":[165]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}