{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T23:03:38Z","timestamp":1774479818038,"version":"3.50.1"},"reference-count":30,"publisher":"World Scientific Pub Co Pte Ltd","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Soft. Eng. Knowl. Eng."],"published-print":{"date-parts":[[2024,3]]},"abstract":"<jats:p> Dialogue generation, as a crucial subtask of dialogue systems, is garnering increasing attention in the field of Natural Language Processing (NLP). The success of dialogue generation relies on effectively utilizing context information to ensure coherent and diverse responses. However, current approaches heavily rely on external sources rather than leveraging the inherent dialogue content. We propose a new approach to address this challenge by introducing semantic segmentation from the field of image processing into NLP.\u00a0Our contribution lies in the development of a Dialogue Generation model with Hierarchical Encoding and Semantic segmentation of dialogue Context, which is called DGHESC.\u00a0This model is topic and speaker-aware, capturing the flow of topic and speaker information within the dialogue context using a hierarchical transformer-based framework. Specifically, we extract semantic information at the word-level for each utterance, segment the dialogue context based on topic and speaker semantics, and employ attention mechanisms to model the context at the utterance-level. Experimental results on two open-domain datasets demonstrate the effectiveness of DGHESC.\u00a0It enhances response quality and achieves state-of-the-art performances on the datasets. <\/jats:p>","DOI":"10.1142\/s0218194024400011","type":"journal-article","created":{"date-parts":[[2024,2,18]],"date-time":"2024-02-18T04:53:00Z","timestamp":1708231980000},"page":"427-447","source":"Crossref","is-referenced-by-count":4,"title":["Dialogue Generation Model with Hierarchical Encoding and Semantic Segmentation of Dialogue Context"],"prefix":"10.1142","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6258-6129","authenticated-orcid":false,"given":"Xiao","family":"Wei","sequence":"first","affiliation":[{"name":"School of Computer Engineering and Science, Shanghai University, Shanghai 200444, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8453-7478","authenticated-orcid":false,"given":"Yidian","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Computer Engineering and Science, Shanghai University, Shanghai 200444, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8190-9796","authenticated-orcid":false,"given":"Qitao","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer Engineering and Science, Shanghai University, Shanghai 200444, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2024,3,23]]},"reference":[{"key":"S0218194024400011BIB001","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.2987064"},{"key":"S0218194024400011BIB002","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P15-1152"},{"key":"S0218194024400011BIB003","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1014"},{"key":"S0218194024400011BIB004","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.9883"},{"key":"S0218194024400011BIB005","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10983"},{"key":"S0218194024400011BIB006","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11965"},{"key":"S0218194024400011BIB007","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1549"},{"key":"S0218194024400011BIB008","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.01.005"},{"key":"S0218194024400011BIB009","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.coling-main.359"},{"key":"S0218194024400011BIB010","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.findings-emnlp.533"},{"key":"S0218194024400011BIB011","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.739"},{"issue":"1","key":"S0218194024400011BIB012","first-page":"33","volume":"23","author":"Hearst M. 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