{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T18:14:52Z","timestamp":1760552092391,"version":"3.37.3"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,4,4]],"date-time":"2024-04-04T00:00:00Z","timestamp":1712188800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["18ZDA237","18AZS006"],"award-info":[{"award-number":["18ZDA237","18AZS006"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>As the capital of Tang Dynasty, Chang\u2019an was one of the most prosperous cities in the world at that time and had a profound influence on Tang poetry. Poets described Chang\u2019an to illustrate the cultural features of the Tang Dynasty while also invoking emotions in readers. The study of Tang Chang\u2019an poetry has important literary and historical value. In order to understand the interpretation and emotional expression of Tang Chang\u2019an poetry more conveniently and clearly, we conducted a study using deep learning to classify Chang\u2019an poetry into four classes: imperially assigned poetry (\u5e94\u5236), emotional poetry (\u611f\u6000), parting poetry (\u79bb\u522b), and other poetry (\u5176\u4ed6). We suggested a comprehensive framework of text classification based on deep learning, including a text input module, feature encoder module, and classification module. We applied several mainstream deep neural network structures to extract features in different ways, which comprised convolutional neural network (CNN), Fasttext, bi-direction long-short-term memory network, and Attention mechanism. Based on our experimental findings, the CNN-based method achieved the best performance for the task. Our inference was that, in Chinese ancient poetry, the analysis of semantic content is more facilitated by local textual features rather than contextual features. We combined this inference with the theory of image in Chinese ancient poetry to analyze the suitability of the deep learning techniques for the study of Chinese ancient poetry.<\/jats:p>","DOI":"10.1093\/llc\/fqae014","type":"journal-article","created":{"date-parts":[[2024,4,4]],"date-time":"2024-04-04T23:57:00Z","timestamp":1712275020000},"page":"756-764","source":"Crossref","is-referenced-by-count":1,"title":["Tang Chang\u2019an poetry automatic classification: a practical application of deep learning methods"],"prefix":"10.1093","volume":"39","author":[{"given":"Mengmeng","family":"Tian","sequence":"first","affiliation":[{"name":"Teachers\u2019 College of Beijing Union University , Beijing, China"}]},{"given":"Qi","family":"Jia","sequence":"additional","affiliation":[{"name":"School of Computer & Communication Engineering, University of Science & Technology Beijing , Beijing, China"}]},{"given":"Cong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Culture Communication and Art, China Women\u2019s University , Beijing, China"}]},{"given":"Juwang","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer & Communication Engineering, University of Science & Technology Beijing , Beijing, China"}]},{"given":"Xin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer & Communication Engineering, University of Science & Technology Beijing , Beijing, China"}]}],"member":"286","published-online":{"date-parts":[[2024,4,4]]},"reference":[{"key":"2024061809545010700_fqae014-B1","doi-asserted-by":"crossref","first-page":"2667","DOI":"10.12928\/telkomnika.v17i5.12646","article-title":"The Classification of the Modern Arabic Poetry Using Machine Learning\u2019","volume":"17","author":"Ahmed","year":"2019","journal-title":"TELKOMNIKA (Telecommunication Computing Electronics and 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