{"id":"https://openalex.org/W3135981671","doi":"https://doi.org/10.1109/bigdata50022.2020.9378495","title":"Deep Neural Query Understanding System at Expedia Group","display_name":"Deep Neural Query Understanding System at Expedia Group","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3135981671","doi":"https://doi.org/10.1109/bigdata50022.2020.9378495","mag":"3135981671"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9378495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","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/A5075676876","display_name":"Ramji Chandrasekaran","orcid":null},"institutions":[{"id":"https://openalex.org/I4210106647","display_name":"Expedia Group (United States)","ror":"https://ror.org/01sh85g09","country_code":"US","type":"company","lineage":["https://openalex.org/I4210106647"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ramji Chandrasekaran","raw_affiliation_strings":["Expedia Group, Seattle, Washington"],"affiliations":[{"raw_affiliation_string":"Expedia Group, Seattle, Washington","institution_ids":["https://openalex.org/I4210106647"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000148676","display_name":"Harsh Nilesh Pathak","orcid":"https://orcid.org/0009-0004-9558-9520"},"institutions":[{"id":"https://openalex.org/I4210106647","display_name":"Expedia Group (United States)","ror":"https://ror.org/01sh85g09","country_code":"US","type":"company","lineage":["https://openalex.org/I4210106647"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Harsh Nilesh Pathak","raw_affiliation_strings":["Expedia Group, Seattle, Washington"],"affiliations":[{"raw_affiliation_string":"Expedia Group, Seattle, Washington","institution_ids":["https://openalex.org/I4210106647"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070657152","display_name":"Tae Yano","orcid":null},"institutions":[{"id":"https://openalex.org/I4210106647","display_name":"Expedia Group (United States)","ror":"https://ror.org/01sh85g09","country_code":"US","type":"company","lineage":["https://openalex.org/I4210106647"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tae Yano","raw_affiliation_strings":["Expedia Group, Seattle, Washington"],"affiliations":[{"raw_affiliation_string":"Expedia Group, Seattle, Washington","institution_ids":["https://openalex.org/I4210106647"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075676876"],"corresponding_institution_ids":["https://openalex.org/I4210106647"],"apc_list":null,"apc_paid":null,"fwci":0.4139,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71802534,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"32","issue":null,"first_page":"1476","last_page":"1484"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.998199999332428,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9972000122070312,"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":0.6982474327087402},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.529294490814209},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.4918336868286133},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4562661647796631},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.28019553422927856}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6982474327087402},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.529294490814209},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.4918336868286133},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4562661647796631},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.28019553422927856},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9378495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","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":51,"referenced_works":["https://openalex.org/W7542544","https://openalex.org/W1522301498","https://openalex.org/W2004763266","https://openalex.org/W2064675550","https://openalex.org/W2068882115","https://openalex.org/W2084070751","https://openalex.org/W2096413109","https://openalex.org/W2120391124","https://openalex.org/W2127589108","https://openalex.org/W2147880316","https://openalex.org/W2155482025","https://openalex.org/W2177726182","https://openalex.org/W2250729567","https://openalex.org/W2296283641","https://openalex.org/W2304209433","https://openalex.org/W2510940142","https://openalex.org/W2542459869","https://openalex.org/W2779888504","https://openalex.org/W2784672094","https://openalex.org/W2785787385","https://openalex.org/W2857028992","https://openalex.org/W2884475480","https://openalex.org/W2896457183","https://openalex.org/W2903158431","https://openalex.org/W2951899185","https://openalex.org/W2953384591","https://openalex.org/W2962739339","https://openalex.org/W2963250244","https://openalex.org/W2963341956","https://openalex.org/W2963756980","https://openalex.org/W2964121744","https://openalex.org/W2964266863","https://openalex.org/W2970049541","https://openalex.org/W2970913210","https://openalex.org/W2973088264","https://openalex.org/W2978017171","https://openalex.org/W2999905431","https://openalex.org/W4252076394","https://openalex.org/W4297808460","https://openalex.org/W6631190155","https://openalex.org/W6677732584","https://openalex.org/W6682082992","https://openalex.org/W6685724381","https://openalex.org/W6713134421","https://openalex.org/W6741277486","https://openalex.org/W6747597888","https://openalex.org/W6747759466","https://openalex.org/W6752909555","https://openalex.org/W6755207826","https://openalex.org/W6756615331","https://openalex.org/W6768851824"],"related_works":["https://openalex.org/W2354970673","https://openalex.org/W2027088687","https://openalex.org/W2737044839","https://openalex.org/W2392467230","https://openalex.org/W2090676757","https://openalex.org/W2304234328","https://openalex.org/W1541456318","https://openalex.org/W2360165400","https://openalex.org/W3118696700","https://openalex.org/W2368709504"],"abstract_inverted_index":{"Understanding":[0,29],"customer":[1],"intent":[2,98],"expressed":[3],"through":[4],"search":[5,82],"queries":[6,42,83],"is":[7],"necessary":[8],"to":[9,17,23,132,136],"not":[10],"only":[11],"provide":[12],"the":[13,85,150],"best":[14],"shopping":[15],"experience":[16],"Expedia":[18],"Group":[19],"customers":[20],"but":[21,141],"also":[22,122],"maximize":[24],"marketing":[25],"returns.":[26],"Natural":[27],"language":[28],"(NLU)":[30],"has":[31],"ubiquitous":[32],"commercial":[33],"application":[34],"in":[35,84],"search,":[36],"conversational":[37],"platforms":[38],"and":[39,47,103,114,162],"more.":[40],"Search":[41],"are":[43],"notoriously":[44],"terse,":[45],"noisy":[46],"lack":[48],"grammatical":[49],"cues":[50],"making":[51],"NLU":[52,78],"a":[53,60],"challenging":[54],"task.":[55],"Multi-lingual":[56],"market":[57],"scalability":[58],"-":[59,68],"highly":[61],"desirable":[62],"feature":[63],"for":[64,80],"global":[65],"travel":[66,86],"agent":[67],"further":[69],"add":[70],"complexity.":[71],"In":[72],"this":[73],"work,":[74],"we":[75],"present":[76],"our":[77,158],"System":[79],"such":[81],"domain":[87],"using":[88],"multi-lingual":[89],"deep":[90],"learning":[91,126,130],"models":[92,135,154],"that":[93,110],"perform":[94],"these":[95,134,153],"broad":[96],"tasks:":[97],"classification,":[99],"named":[100],"entity":[101],"recognition":[102,113],"linking.":[104],"We":[105,148],"propose":[106],"an":[107],"alternate":[108],"framework":[109],"significantly":[111],"improves":[112],"resolution":[115],"of":[116,157],"ill-defined":[117],"sparse":[118],"entities.":[119],"Our":[120],"system":[121],"includes":[123],"cross-lingual":[124],"transfer":[125],"components":[127],"featuring":[128],"active":[129],"loop":[131],"scale":[133],"multiple":[137],"languages":[138],"with":[139],"minimal":[140],"high":[142],"quality":[143],"annotation":[144],"by":[145],"localization":[146],"experts.":[147],"explain":[149],"business":[151],"problem":[152],"address,":[155],"idiosyncrasies":[156],"data,":[159],"architecture":[160],"details":[161],"implementation":[163],"trade-offs.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}