{"id":"https://openalex.org/W3210854429","doi":"https://doi.org/10.3233/faia210185","title":"Multi-Granularity and Internal-External Correlation Residual Model for Chinese Sentence Semantic Matching","display_name":"Multi-Granularity and Internal-External Correlation Residual Model for Chinese Sentence Semantic Matching","publication_year":2021,"publication_date":"2021-10-14","ids":{"openalex":"https://openalex.org/W3210854429","doi":"https://doi.org/10.3233/faia210185","mag":"3210854429"},"language":"en","primary_location":{"id":"doi:10.3233/faia210185","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia210185","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA210185","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA210185","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100322310","display_name":"Lan Zhang","orcid":"https://orcid.org/0000-0002-7718-6128"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lan Zhang","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, Kunming 650091, China","School of Information Science and Engineering, Yunnan University, Kunming 650091, China;"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming 650091, China","institution_ids":["https://openalex.org/I189210763"]},{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming 650091, China;","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100358456","display_name":"Hongmei Chen","orcid":"https://orcid.org/0000-0002-4054-3654"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongmei Chen","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, Kunming 650091, China","School of Information Science and Engineering, Yunnan University, Kunming 650091, China;"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming 650091, China","institution_ids":["https://openalex.org/I189210763"]},{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming 650091, China;","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100358456"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2368336,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9976999759674072,"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":0.9976999759674072,"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":0.9959999918937683,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.902999997138977,"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":0.7657406330108643},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7345870733261108},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.7261317372322083},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6260558366775513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6235384941101074},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5638365149497986},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.55159991979599},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.549505352973938},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5051265358924866},{"id":"https://openalex.org/keywords/semantic-matching","display_name":"Semantic matching","score":0.4451427459716797},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1649239957332611},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10959231853485107},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09110376238822937}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7657406330108643},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7345870733261108},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.7261317372322083},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6260558366775513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6235384941101074},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5638365149497986},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.55159991979599},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.549505352973938},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5051265358924866},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.4451427459716797},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1649239957332611},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10959231853485107},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09110376238822937},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia210185","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia210185","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA210185","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia210185","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia210185","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA210185","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3210854429.pdf","grobid_xml":"https://content.openalex.org/works/W3210854429.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1722903425","https://openalex.org/W2131774270","https://openalex.org/W2131876387","https://openalex.org/W2170738476","https://openalex.org/W2267186426","https://openalex.org/W2286300105","https://openalex.org/W2593833795","https://openalex.org/W2598285986","https://openalex.org/W2605179600","https://openalex.org/W2608787653","https://openalex.org/W2756386045","https://openalex.org/W2876111955","https://openalex.org/W2889968917","https://openalex.org/W2896457183","https://openalex.org/W2904664992","https://openalex.org/W2951359136","https://openalex.org/W2953075226","https://openalex.org/W2964082993","https://openalex.org/W2965373594","https://openalex.org/W2970641574","https://openalex.org/W2971871542","https://openalex.org/W2973840669","https://openalex.org/W3012568767","https://openalex.org/W3021715678","https://openalex.org/W3118205297","https://openalex.org/W4239019441","https://openalex.org/W4294170691","https://openalex.org/W6679257740"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W4256502920","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2999756192","https://openalex.org/W4382701072","https://openalex.org/W3196281958","https://openalex.org/W1595649729"],"abstract_inverted_index":{"Sentence":[0],"semantic":[1,20,32,63,84,140],"matching":[2,21,48],"(SSM)":[3],"is":[4,13,56,108],"central":[5],"to":[6,23,37,50,60,79,87,100,110,137,147],"many":[7],"natural":[8],"language":[9],"processing":[10],"tasks.":[11],"This":[12,68],"especially":[14],"the":[15,24,27,82,89,94,112,123,143,148,156,170],"case":[16],"for":[17,65,162],"Chinese":[18,66,163],"sentence":[19],"due":[22],"complexity":[25],"of":[26],"semantics,":[28],"missing":[29,90],"semantics":[30,91],"and":[31,46,73,86,122],"confusion":[33],"are":[34],"more":[35,139],"likely":[36],"occur.":[38],"Existing":[39],"methods":[40],"have":[41],"used":[42],"enhanced":[43],"text":[44],"representations":[45],"multiple":[47],"strategies":[49],"address":[51],"these":[52],"problems":[53],"but":[54],"there":[55],"still":[57],"great":[58],"potential":[59],"capture":[61,81,101],"deep":[62,83],"information":[64,85,141],"text.":[67],"paper":[69],"proposes":[70],"a":[71,117],"Multi-Granularity":[72],"Internal-External":[74],"correlation":[75,113,124],"Residual":[76],"model":[77,96],"(MGIER)":[78],"better":[80,174],"alleviate":[88],"effectively.":[92],"First,":[93],"MGIER":[95],"utilizes":[97],"character/word":[98],"granularity":[99],"fine-grained":[102],"information.":[103],"Then,":[104],"soft":[105],"alignment":[106],"attention":[107],"employed":[109],"enhance":[111],"between":[114,125],"characters/words":[115],"in":[116],"sentence,":[118],"called":[119,127],"internal":[120],"correlation,":[121],"sentences,":[126],"external":[128],"correlation.":[129],"In":[130],"particular,":[131],"this":[132],"method":[133,158,171],"uses":[134],"residual":[135],"connections":[136],"preserve":[138],"from":[142],"bottom":[144],"embedding":[145],"layer":[146],"top":[149],"prediction":[150],"layer.":[151],"Experimental":[152],"results":[153],"show":[154],"that":[155],"proposed":[157],"achieves":[159,173],"state-of-the-art":[160],"performance":[161,175],"SSM,":[164],"and,":[165],"compared":[166],"with":[167,176],"pre-trained":[168],"models,":[169],"also":[172],"fewer":[177],"parameters.":[178]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
