{"id":"https://openalex.org/W2963087152","doi":"https://doi.org/10.1109/bigdata.2017.8258025","title":"Bringing semantic structures to user intent detection in online medical queries","display_name":"Bringing semantic structures to user intent detection in online medical queries","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2963087152","doi":"https://doi.org/10.1109/bigdata.2017.8258025","mag":"2963087152"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2017.8258025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258025","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5017147857","display_name":"Chenwei Zhang","orcid":"https://orcid.org/0000-0002-0488-4603"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chenwei Zhang","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100721790","display_name":"Nan Du","orcid":"https://orcid.org/0000-0003-2855-7452"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nan Du","raw_affiliation_strings":["Baidu Research Big Data Lab, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"Baidu Research Big Data Lab, Sunnyvale, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380588","display_name":"Wei Fan","orcid":"https://orcid.org/0009-0008-1900-7081"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Fan","raw_affiliation_strings":["Tencent Medical AI Lab, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent Medical AI Lab, Palo Alto, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046576694","display_name":"Yaliang Li","orcid":"https://orcid.org/0000-0002-4204-6096"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yaliang Li","raw_affiliation_strings":["Baidu Research Big Data Lab, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"Baidu Research Big Data Lab, Sunnyvale, CA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024393012","display_name":"Chun-Ta Lu","orcid":"https://orcid.org/0000-0001-8573-4975"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chun-Ta Lu","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036357902","display_name":"Philip S. Yu","orcid":"https://orcid.org/0000-0002-3491-5968"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Philip S. Yu","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","Institute for Data Science, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"Institute for Data Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5017147857"],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":1.1701,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.85054943,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1019","last_page":"1026"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9976000189781189,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9970999956130981,"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":0.7766712307929993},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5989407300949097},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5434600710868835},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.49489229917526245},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4884616434574127},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.47491559386253357},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4546126127243042},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.42022523283958435},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.3207683265209198},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2993335723876953},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29599088430404663}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7766712307929993},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5989407300949097},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5434600710868835},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.49489229917526245},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4884616434574127},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.47491559386253357},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4546126127243042},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.42022523283958435},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3207683265209198},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2993335723876953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29599088430404663},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2017.8258025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258025","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7200000286102295,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320318547","display_name":"Baidu","ror":"https://ror.org/03vs3wt56"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W55768394","https://openalex.org/W154397242","https://openalex.org/W1503398984","https://openalex.org/W1522301498","https://openalex.org/W1529533208","https://openalex.org/W1533861849","https://openalex.org/W1924770834","https://openalex.org/W1982498087","https://openalex.org/W2037933327","https://openalex.org/W2054290230","https://openalex.org/W2063272642","https://openalex.org/W2064675550","https://openalex.org/W2069143585","https://openalex.org/W2090031974","https://openalex.org/W2107878631","https://openalex.org/W2120615054","https://openalex.org/W2127795553","https://openalex.org/W2128296282","https://openalex.org/W2130942839","https://openalex.org/W2153579005","https://openalex.org/W2157331557","https://openalex.org/W2250473310","https://openalex.org/W2265846598","https://openalex.org/W2295951523","https://openalex.org/W2337562570","https://openalex.org/W2523625823","https://openalex.org/W2585939463","https://openalex.org/W2962883855","https://openalex.org/W2963087152","https://openalex.org/W2963161738","https://openalex.org/W2964121744","https://openalex.org/W4232932184","https://openalex.org/W4294170691","https://openalex.org/W6606185422","https://openalex.org/W6631943919","https://openalex.org/W6640400011","https://openalex.org/W6678830454","https://openalex.org/W6679436768","https://openalex.org/W6682691769","https://openalex.org/W6691776601","https://openalex.org/W6693505360"],"related_works":["https://openalex.org/W2337562570","https://openalex.org/W2003068264","https://openalex.org/W3017033364","https://openalex.org/W2964071174","https://openalex.org/W2963341956","https://openalex.org/W2064675550","https://openalex.org/W1994965736","https://openalex.org/W2946546614","https://openalex.org/W2006378146","https://openalex.org/W3186669500","https://openalex.org/W2982244969","https://openalex.org/W74857346","https://openalex.org/W2106114815","https://openalex.org/W1504736497","https://openalex.org/W2406724607","https://openalex.org/W2203598687","https://openalex.org/W2095356390","https://openalex.org/W3139197683","https://openalex.org/W2068070248","https://openalex.org/W2067658744"],"abstract_inverted_index":{"The":[0,16],"Internet":[1],"has":[2],"revolutionized":[3],"healthcare":[4,17,52],"by":[5,186],"offering":[6],"medical":[7,20,32,70,89,96,105,130,161,204],"information":[8,21,45,53],"ubiquitously":[9],"to":[10,36,61,78,117,149,164],"patients":[11,24],"via":[12],"the":[13,126,156,165,188,192,197],"web":[14],"search.":[15],"status,":[18],"complex":[19],"needs":[22],"of":[23,42,158,167],"are":[25],"expressed":[26,69],"diversely":[27,68],"and":[28,47,99,153,179],"implicitly":[29],"in":[30,88,177,183],"their":[31,51,67],"text":[33,71,205],"queries.":[34,72,206],"Aiming":[35],"better":[37],"capture":[38],"a":[39,75,95,104,160,168],"focused":[40],"picture":[41],"user's":[43],"medical-related":[44],"search":[46],"shed":[48],"insights":[49],"on":[50,112,202],"access":[54],"strategies,":[55],"it":[56],"is":[57,115,147],"challenging":[58],"yet":[59],"rewarding":[60],"detect":[62],"structured":[63,80,119],"user":[64,85,123],"intentions":[65],"from":[66,122],"We":[73,171],"introduce":[74],"graph-based":[76,142],"formulation":[77],"explore":[79],"concept":[81,97,106,131,137,162,198],"transitions":[82,121,138],"for":[83,196],"effective":[84],"intent":[86],"detection":[87],"queries,":[90,124],"where":[91,125],"each":[92,100],"node":[93],"represents":[94],"mention":[98],"directed":[101],"edge":[102],"indicates":[103],"transition.":[107,170],"A":[108,140],"deep":[109],"model":[110,127,190,195],"based":[111],"multi-task":[113],"learning":[114],"introduced":[116],"extract":[118],"semantic":[120,169],"extracts":[128],"word-level":[129],"mentions":[132],"as":[133,135],"well":[134],"sentence-level":[136],"collectively.":[139],"customized":[141],"mutual":[143],"transfer":[144],"loss":[145],"function":[146],"designed":[148],"impose":[150],"explicit":[151],"constraints":[152],"further":[154],"exploit":[155],"contribution":[157],"mentioning":[159],"word":[163],"implication":[166],"observe":[172],"an":[173],"8%":[174],"relative":[175,181],"improvement":[176],"AUC":[178],"23%":[180],"reduction":[182],"coverage":[184],"error":[185],"comparing":[187],"proposed":[189],"with":[191],"best":[193],"baseline":[194],"transition":[199],"inference":[200],"task":[201],"real-world":[203]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
