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This increase helps cover more population by using fewer resources for mental health treatments. Adaptivity and customization for the remedy routine can help solve mental health issues quickly. In this research, we propose a fuzzy contrast-based model that uses an attention network for positional weighted words and classifies mental patient authored text into distinct symptoms. After that, the trained embedding is used to label mental data. Then the attention network expands its lexicons to adapt to the usage of transfer learning techniques. The proposed model uses similarity and contrast sets to classify the weighted attention words. The fuzzy model then uses the sets to classify the mental health data into distinct classes. Our method is compared with non-embedding and traditional techniques to demonstrate the proposed model. From the experiments, the feature vector can achieve a high ROC curve of 0.82 with problems associated with nine symptoms.<\/jats:p>","DOI":"10.1145\/3506701","type":"journal-article","created":{"date-parts":[[2022,2,3]],"date-time":"2022-02-03T17:54:50Z","timestamp":1643910890000},"page":"1-16","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["Fuzzy Contrast Set Based Deep Attention Network for Lexical Analysis and Mental Health Treatment"],"prefix":"10.1145","volume":"21","author":[{"given":"Usman","family":"Ahmed","sequence":"first","affiliation":[{"name":"Western Norway University of Applied Sciences, Bergen, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8768-9709","authenticated-orcid":false,"given":"Jerry Chun-Wei","family":"Lin","sequence":"additional","affiliation":[{"name":"Western Norway University of Applied Sciences, Bergen, Norway"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9851-4103","authenticated-orcid":false,"given":"Gautam","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Brandon University, Canada and China Medical University, Taichung, Taiwan"}]}],"member":"320","published-online":{"date-parts":[[2022,4,29]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/FUZZ45933.2021.9494423"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2021.642347"},{"key":"e_1_3_2_4_2","first-page":"24","volume-title":"The International Conference on Learning Representations","author":"Bahdanau Dzmitry","year":"2015","unstructured":"Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015. 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