{"id":"https://openalex.org/W4391918045","doi":"https://doi.org/10.1142/s0218194024400011","title":"Dialogue Generation Model with Hierarchical Encoding and Semantic Segmentation of Dialogue Context","display_name":"Dialogue Generation Model with Hierarchical Encoding and Semantic Segmentation of Dialogue Context","publication_year":2024,"publication_date":"2024-02-18","ids":{"openalex":"https://openalex.org/W4391918045","doi":"https://doi.org/10.1142/s0218194024400011"},"language":"en","primary_location":{"id":"doi:10.1142/s0218194024400011","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218194024400011","pdf_url":null,"source":{"id":"https://openalex.org/S131442419","display_name":"International Journal of Software Engineering and Knowledge Engineering","issn_l":"0218-1940","issn":["0218-1940","1793-6403"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Software Engineering and Knowledge Engineering","raw_type":"journal-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/A5101703681","display_name":"Xiao Wei","orcid":"https://orcid.org/0000-0002-6258-6129"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Wei","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai 200444, P.\u00a0R.\u00a0China"],"raw_orcid":"https://orcid.org/0000-0002-6258-6129","affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai 200444, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102006887","display_name":"Yidian Lin","orcid":"https://orcid.org/0000-0001-8453-7478"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yidian Lin","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai 200444, P.\u00a0R.\u00a0China"],"raw_orcid":"https://orcid.org/0000-0001-8453-7478","affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai 200444, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102864387","display_name":"Qitao Hu","orcid":"https://orcid.org/0009-0009-8190-9796"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qitao Hu","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai 200444, P.\u00a0R.\u00a0China"],"raw_orcid":"https://orcid.org/0009-0009-8190-9796","affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai 200444, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I141962983"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5102864387"],"corresponding_institution_ids":["https://openalex.org/I141962983"],"apc_list":null,"apc_paid":null,"fwci":1.1114,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.7960563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"34","issue":"03","first_page":"427","last_page":"447"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.9639999866485596,"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/T12031","display_name":"Speech and dialogue systems","score":0.9639999866485596,"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":0.9059000015258789,"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":0.7056057453155518},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6678448915481567},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6471989750862122},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6283971667289734},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.622264564037323},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4891548454761505},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.4310012757778168},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07093438506126404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7056057453155518},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6678448915481567},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6471989750862122},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6283971667289734},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.622264564037323},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4891548454761505},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.4310012757778168},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07093438506126404},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218194024400011","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218194024400011","pdf_url":null,"source":{"id":"https://openalex.org/S131442419","display_name":"International Journal of Software Engineering and Knowledge Engineering","issn_l":"0218-1940","issn":["0218-1940","1793-6403"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Software Engineering and Knowledge Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2584185835","https://openalex.org/W2587838525","https://openalex.org/W2741363662","https://openalex.org/W2951114218","https://openalex.org/W2962883855","https://openalex.org/W2962896208","https://openalex.org/W2963206148","https://openalex.org/W2963879591","https://openalex.org/W2963963856","https://openalex.org/W2970641574","https://openalex.org/W2988937804","https://openalex.org/W3022187094","https://openalex.org/W3024507639","https://openalex.org/W3034999214","https://openalex.org/W3035451444","https://openalex.org/W3098641803","https://openalex.org/W3109558947","https://openalex.org/W3116191565","https://openalex.org/W4206573688","https://openalex.org/W4225107720","https://openalex.org/W4283798957","https://openalex.org/W4287889589","https://openalex.org/W4385574423"],"related_works":["https://openalex.org/W2349222429","https://openalex.org/W3117430770","https://openalex.org/W2116230991","https://openalex.org/W2590751808","https://openalex.org/W2132709506","https://openalex.org/W1972377868","https://openalex.org/W2186895195","https://openalex.org/W2388933862","https://openalex.org/W2744694118","https://openalex.org/W1599026413"],"abstract_inverted_index":{"Dialogue":[0,82],"generation,":[1],"as":[2],"a":[3,55,81,117],"crucial":[4],"subtask":[5],"of":[6,16,23,69,80,91,107,162],"dialogue":[7,24,51,92,114,134],"systems,":[8],"is":[9,95,100],"garnering":[10],"increasing":[11],"attention":[12,144],"in":[13,77],"the":[14,49,67,78,105,113,127,133,148,151,160,173],"field":[15,68],"Natural":[17],"Language":[18],"Processing":[19],"(NLP).":[20],"The":[21],"success":[22],"generation":[25],"relies":[26],"on":[27,43,137,155,172],"effectively":[28],"utilizing":[29],"context":[30,115,135,149],"information":[31,111,125],"to":[32,58,146],"ensure":[33],"coherent":[34],"and":[35,88,102,109,139,142,168],"diverse":[36],"responses.":[37],"However,":[38],"current":[39],"approaches":[40],"heavily":[41],"rely":[42],"external":[44],"sources":[45],"rather":[46],"than":[47],"leveraging":[48],"inherent":[50],"content.":[52],"We":[53],"propose":[54],"new":[56],"approach":[57],"address":[59],"this":[60],"challenge":[61],"by":[62],"introducing":[63],"semantic":[64,124],"segmentation":[65,90],"from":[66],"image":[70],"processing":[71],"into":[72],"NLP.":[73],"Our":[74],"contribution":[75],"lies":[76],"development":[79],"Generation":[83],"model":[84,99,147],"with":[85],"Hierarchical":[86],"Encoding":[87],"Semantic":[89],"Context,":[93],"which":[94],"called":[96],"DGHESC.":[97,163],"This":[98],"topic":[101,108,138],"speaker-aware,":[103],"capturing":[104],"flow":[106],"speaker":[110,140],"within":[112],"using":[116],"hierarchical":[118],"transformer-based":[119],"framework.":[120],"Specifically,":[121],"we":[122],"extract":[123],"at":[126,150],"word-level":[128],"for":[129],"each":[130],"utterance,":[131],"segment":[132],"based":[136],"semantics,":[141],"employ":[143],"mechanisms":[145],"utterance-level.":[152],"Experimental":[153],"results":[154],"two":[156],"open-domain":[157],"datasets":[158],"demonstrate":[159],"effectiveness":[161],"It":[164],"enhances":[165],"response":[166],"quality":[167],"achieves":[169],"state-of-the-art":[170],"performances":[171],"datasets.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}