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To increase the availability of short texts in real applications, we propose a Label Information Assisting-based Model (LIAM) for Chinese short text classification. In the model, we jointly use sentence-level features and word-level features to reduce text information loss. And the sentence-level features are fused with relevant label information by the Label Information Extending and Fusion (LIEF) module while the word-level features are also enhanced with assistance of relevant label information. By utilizing the text-related information from labels as extended information, the model enriches and enhances the features of short text, benefiting classification. To verify the correctness and effectiveness of the proposed method, we conduct extensive experiments on four Chinese datasets and six sub-datasets with different models. The experimental results show that LIAM presented can effectively enrich information for text and much improve the performance of short text classification. It performs much better than other methods do. What is more, the less the training set, the greater the advantages of the model.<\/jats:p>","DOI":"10.1145\/3582301","type":"journal-article","created":{"date-parts":[[2023,2,8]],"date-time":"2023-02-08T13:25:15Z","timestamp":1675862715000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Short Text Classification of Chinese with Label Information Assisting"],"prefix":"10.1145","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9934-2825","authenticated-orcid":false,"given":"Qianqian","family":"Xu","sequence":"first","affiliation":[{"name":"School of Computer Engineering and Science, Shanghai University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1046-4496","authenticated-orcid":false,"given":"Junjie","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer Engineering and Science &amp; Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9591-390X","authenticated-orcid":false,"given":"Cangzhi","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Computer Engineering and Science, Shanghai University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8824-6122","authenticated-orcid":false,"given":"Shuhua","family":"Tan","sequence":"additional","affiliation":[{"name":"National Engineering Laboratory for Logistics Information Technology, YTO Express Co., Ltd., Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2404-3174","authenticated-orcid":false,"given":"Fen","family":"Yi","sequence":"additional","affiliation":[{"name":"National Engineering Laboratory for Logistics Information Technology, YTO Express Co., Ltd., Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7420-3703","authenticated-orcid":false,"given":"Feng","family":"Cheng","sequence":"additional","affiliation":[{"name":"Hasso Plattner Institute, University of Potsdam, Germany"}]}],"member":"320","published-online":{"date-parts":[[2023,3,25]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"6252","volume-title":"The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019","author":"Chen Jindong","year":"2019","unstructured":"Jindong Chen, Yizhou Hu, Jingping Liu, Yanghua Xiao, and Haiyun Jiang. 2019. 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