{"id":"https://openalex.org/W4392255665","doi":"https://doi.org/10.1145/3633637.3633711","title":"Multi-perspective Text Matching Algorithm Based on Multi-granularity Feature Convolution","display_name":"Multi-perspective Text Matching Algorithm Based on Multi-granularity Feature Convolution","publication_year":2023,"publication_date":"2023-10-27","ids":{"openalex":"https://openalex.org/W4392255665","doi":"https://doi.org/10.1145/3633637.3633711"},"language":"en","primary_location":{"id":"doi:10.1145/3633637.3633711","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3633637.3633711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 12th International Conference on Computing and Pattern Recognition","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/A5008213911","display_name":"Baohua Qiang","orcid":"https://orcid.org/0000-0002-3469-6590"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Baohua Qiang","raw_affiliation_strings":["Guilin University of Electronic Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-3469-6590","affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007233153","display_name":"Zhiwen Guo","orcid":"https://orcid.org/0009-0004-0508-0342"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwen Guo","raw_affiliation_strings":["Guilin University of Electronic Technology, China"],"raw_orcid":"https://orcid.org/0009-0004-0508-0342","affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079435030","display_name":"Guangyong Xi","orcid":"https://orcid.org/0000-0002-1163-4565"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangyong Xi","raw_affiliation_strings":["Guilin University of Electronic Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-1163-4565","affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080734422","display_name":"Shuiping Guo","orcid":"https://orcid.org/0009-0000-3633-2515"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuiping Guo","raw_affiliation_strings":["The 7th Research Institute of CETC, China"],"raw_orcid":"https://orcid.org/0009-0000-3633-2515","affiliations":[{"raw_affiliation_string":"The 7th Research Institute of CETC, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083855372","display_name":"Y. Wang","orcid":"https://orcid.org/0009-0005-7896-3274"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yufeng Wang","raw_affiliation_strings":["The 54th Research Institute of CETC, China"],"raw_orcid":"https://orcid.org/0009-0005-7896-3274","affiliations":[{"raw_affiliation_string":"The 54th Research Institute of CETC, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067186052","display_name":"Xianyi Yang","orcid":"https://orcid.org/0000-0002-9026-7934"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianyi Yang","raw_affiliation_strings":["Guilin University of Electronic Technology, China"],"raw_orcid":"https://orcid.org/0000-0002-9026-7934","affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology, China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010586297","display_name":"Yuemeng Wang","orcid":"https://orcid.org/0009-0001-8112-1693"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuemeng Wang","raw_affiliation_strings":["The 54th Research Institute of CETC, China"],"raw_orcid":"https://orcid.org/0009-0001-8112-1693","affiliations":[{"raw_affiliation_string":"The 54th Research Institute of CETC, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5008213911"],"corresponding_institution_ids":["https://openalex.org/I5343935"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20888091,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"469","last_page":"474"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9958999752998352,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9958999752998352,"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/T10028","display_name":"Topic Modeling","score":0.9839000105857849,"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/T13904","display_name":"Artificial Intelligence Applications","score":0.9646999835968018,"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/granularity","display_name":"Granularity","score":0.8483984470367432},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8218016624450684},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5755355954170227},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48597654700279236},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4755789339542389},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.44605591893196106},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4265492558479309},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4147534668445587},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40036237239837646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39835867285728455},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09596478939056396}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.8483984470367432},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8218016624450684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5755355954170227},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48597654700279236},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4755789339542389},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.44605591893196106},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4265492558479309},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4147534668445587},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40036237239837646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39835867285728455},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09596478939056396},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3633637.3633711","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3633637.3633711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 12th International Conference on Computing and Pattern Recognition","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":14,"referenced_works":["https://openalex.org/W55204438","https://openalex.org/W2184652140","https://openalex.org/W2217433794","https://openalex.org/W2483327705","https://openalex.org/W2608239929","https://openalex.org/W2741609678","https://openalex.org/W3128872869","https://openalex.org/W3166806411","https://openalex.org/W4230858134","https://openalex.org/W4288048729","https://openalex.org/W4292607650","https://openalex.org/W4308931255","https://openalex.org/W4403577524","https://openalex.org/W6603989641"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W4256502920","https://openalex.org/W4382701072"],"abstract_inverted_index":{"The":[0,80,166],"core":[1],"of":[2,42,49,60,138,147,162,172],"Chinese":[3,64],"text":[4,44,65,71,193],"matching":[5,59,72,155,194],"task":[6],"lies":[7],"in":[8,63,111,169],"mining":[9],"the":[10,15,18,29,40,107,112,131,136,143,159,170,188],"deep":[11],"semantic":[12,19,30,51,109,140],"information":[13,52,110],"inside":[14],"text,":[16],"exploring":[17],"similarities":[20],"and":[21,26,56,86,92,123,179],"differences":[22],"between":[23,32],"different":[24],"texts,":[25],"then":[27,96],"analyzing":[28],"similarity":[31],"two":[33,148],"texts":[34,149],"to":[35,104,129,134,157],"be":[36],"matched.":[37],"To":[38],"address":[39],"problems":[41],"single":[43],"granularity":[45,132],"feature,":[46],"insufficient":[47],"capture":[48,130],"potential":[50],"at":[53],"multiple":[54],"granularities":[55],"weak":[57],"interactive":[58],"coding":[61],"features":[62,77,133],"matching,":[66],"we":[67],"propose":[68],"a":[69,98,115,174,181],"multi-perspective":[70,154],"model":[73,81],"based":[74],"on":[75],"multi-granularity":[76,139,144,163],"convolution":[78],"(MpmMfc).":[79],"first":[82],"extracts":[83],"characters,":[84],"words":[85],"associated":[87],"phrases":[88],"by":[89,153],"multi-pattern":[90],"partitioning":[91],"performs":[93],"initial":[94],"encoding,":[95],"uses":[97],"two-way":[99],"gate":[100],"loop":[101],"control":[102],"unit":[103],"initially":[105],"extract":[106],"contextual":[108],"encoding.":[113],"Then":[114],"multi-grain":[116],"size":[117],"high-dimensional":[118],"encoding":[119],"matrix":[120],"is":[121,127],"constructed":[122],"convolutional":[124,145],"neural":[125],"network":[126],"used":[128],"improve":[135],"characterization":[137],"information.":[141,165],"Finally,":[142],"matrices":[146],"are":[150,185],"cross-cosine":[151],"matched":[152],"patterns":[156],"enhance":[158],"interaction":[160],"strength":[161],"feature":[164],"results":[167],"achieved":[168],"experiments":[171],"LCQMC,":[173],"spoken":[175],"expression":[176],"class":[177,183],"dataset,":[178,184],"BQ,":[180],"financial":[182],"better":[186],"than":[187],"currently":[189],"available":[190],"non-BERT":[191],"type":[192],"models.":[195]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
