{"id":"https://openalex.org/W4385691563","doi":"https://doi.org/10.1145/3605801.3605806","title":"Application of large language model in intelligent Q&A of digital government","display_name":"Application of large language model in intelligent Q&A of digital government","publication_year":2023,"publication_date":"2023-06-16","ids":{"openalex":"https://openalex.org/W4385691563","doi":"https://doi.org/10.1145/3605801.3605806"},"language":"en","primary_location":{"id":"doi:10.1145/3605801.3605806","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3605801.3605806","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 2nd International Conference on Networks, Communications and Information Technology","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/A5103026062","display_name":"Shangsheng Gao","orcid":"https://orcid.org/0009-0005-7444-627X"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shangsheng Gao","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047801985","display_name":"Li Gao","orcid":"https://orcid.org/0009-0001-2371-4351"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Gao","raw_affiliation_strings":["Beijing Caizhi Technology Co., Ltd., China"],"affiliations":[{"raw_affiliation_string":"Beijing Caizhi Technology Co., Ltd., China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103250856","display_name":"Qi Li","orcid":"https://orcid.org/0009-0006-2180-4157"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi Li","raw_affiliation_strings":["Beijing Caizhi Technology Co., Ltd., China"],"affiliations":[{"raw_affiliation_string":"Beijing Caizhi Technology Co., Ltd., China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101531222","display_name":"Jianjun Xu","orcid":"https://orcid.org/0009-0003-7812-7212"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianjun Xu","raw_affiliation_strings":["Beijing Caizhi Technology Co., Ltd., China"],"affiliations":[{"raw_affiliation_string":"Beijing Caizhi Technology Co., Ltd., China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103026062"],"corresponding_institution_ids":["https://openalex.org/I4210114105"],"apc_list":null,"apc_paid":null,"fwci":1.5657,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.86369451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"24","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9868999719619751,"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":0.9868999719619751,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9825999736785889,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9815000295639038,"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":0.8191086053848267},{"id":"https://openalex.org/keywords/premise","display_name":"Premise","score":0.725551962852478},{"id":"https://openalex.org/keywords/government","display_name":"Government (linguistics)","score":0.6829015612602234},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.6488847136497498},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5949183106422424},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.567361056804657},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5153900384902954},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4787299335002899},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4762425720691681},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4318614602088928},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3380875885486603},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11132046580314636},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.10014978051185608}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8191086053848267},{"id":"https://openalex.org/C2778023277","wikidata":"https://www.wikidata.org/wiki/Q321703","display_name":"Premise","level":2,"score":0.725551962852478},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.6829015612602234},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.6488847136497498},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5949183106422424},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.567361056804657},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5153900384902954},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4787299335002899},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4762425720691681},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4318614602088928},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3380875885486603},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11132046580314636},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.10014978051185608},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3605801.3605806","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3605801.3605806","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 2nd International Conference on Networks, Communications and Information Technology","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":4,"referenced_works":["https://openalex.org/W1593271688","https://openalex.org/W2136189984","https://openalex.org/W3097594135","https://openalex.org/W4212860634"],"related_works":["https://openalex.org/W590788508","https://openalex.org/W4235873430","https://openalex.org/W2611974471","https://openalex.org/W4313233093","https://openalex.org/W2358082531","https://openalex.org/W2589976903","https://openalex.org/W2335596023","https://openalex.org/W2026719400","https://openalex.org/W2374273535","https://openalex.org/W4225892616"],"abstract_inverted_index":{"LLM":[0,15],"(Large":[1],"Language":[2],"Model)":[3],"is":[4,10,28,55,96,108,112,170],"developing":[5],"rapidly":[6],"today,":[7],"and":[8,40,49,60,99,101,141],"it":[9,76,143,164,169],"very":[11],"important":[12],"to":[13,16,57,136],"use":[14,43],"help":[17,137],"existing":[18,146],"question":[19,25,119,148],"answering":[20,26,120,149],"systems":[21],"improve.":[22],"The":[23],"government":[24,34,94,147],"system":[27,121,177],"of":[29,46,68,82,88,93,105,154,159],"great":[30,180],"value":[31],"in":[32,65,90],"improving":[33],"administrative":[35],"efficiency.":[36],"Existing":[37],"intelligent":[38],"questions":[39,107],"answers":[41],"mostly":[42],"the":[44,80,86,91,102,110,118,129,145,152,157,160,175,184],"combination":[45],"keyword":[47,53,124],"matching":[48,54],"machine":[50,73],"learning.":[51],"But":[52],"difficult":[56,98],"understand":[58,138],"complex":[59],"multi-round":[61],"dialogue":[62],"questions,":[63,140],"resulting":[64],"limited":[66],"quality":[67],"reply":[69],"content.":[70],"Based":[71],"on":[72,123],"learning":[74],"method,":[75],"has":[77,178],"further":[78],"improved":[79],"understanding":[81,87],"semantics,":[83],"but":[84],"because":[85],"words":[89],"field":[92],"affairs":[95],"too":[97],"professional;":[100],"semantic":[103],"recognition":[104],"colloquial":[106],"difficult,":[109],"performance":[111],"not":[113],"even":[114],"as":[115,117,133],"good":[116],"based":[122],"matching.":[125],"This":[126],"paper":[127],"uses":[128],"large":[130,161],"language":[131,162],"model":[132],"a":[134,179],"tool":[135],"user":[139],"integrates":[142],"into":[144],"system.":[150],"On":[151],"premise":[153],"effectively":[155],"utilizing":[156],"advantages":[158],"model,":[163],"avoids":[165],"its":[166],"defects.":[167],"And":[168],"demonstrated":[171],"by":[172],"experiments":[173],"that":[174],"above":[176],"improvement":[181],"compared":[182],"with":[183],"previous":[185],"method.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}