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The model involves two stacked Bi-LSTM modules and an information interaction component to generate all opinion-polarity pairs of the input sentences simultaneously. The experimental results show that our model achieves advanced results in target opinion word-polarity co-extraction. The performance of both tasks is stronger than the baseline, and the model is of low complexity and high operational efficiency. <\/jats:p>","DOI":"10.1142\/s0219649222500976","type":"journal-article","created":{"date-parts":[[2023,2,24]],"date-time":"2023-02-24T11:50:45Z","timestamp":1677239445000},"source":"Crossref","is-referenced-by-count":0,"title":["A Joint Model for Target-Oriented Opinion Words Extraction and Sentiment Classification"],"prefix":"10.1142","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4596-4850","authenticated-orcid":false,"given":"Chenyang","family":"Dai","sequence":"first","affiliation":[{"name":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, P. R. China"}]},{"given":"Bo","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, P. R. 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