{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:15:44Z","timestamp":1777706144498,"version":"3.51.4"},"reference-count":31,"publisher":"SAGE Publications","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2023,8,1]]},"abstract":"<jats:p>To address the problem that single-channel neural networks cannot fully extract text semantic features in traditional user portrait construction methods, this paper proposes a dual-channel user portrait model based on DPCNN-BIGRU and attention mechanism. The model first uses Bidirectional Encoder Representation from Transformers(Bert) and CK-means+ to obtain the fusion vector of semantic features and topic features, and then feeds the vector into Deep Pyramid Convolutional Neural Networks (DPCNN) and Bidirectional Gated Recurrent Unit (BiGRU). Deep features and global features of the text are obtained simultaneously, and then weights are assigned by the attention mechanism. Finally, the output features of the dual channels are fused and classified. It is tested on the Sogou user portrait datasets, and the experimental results prove that the dual-channel model outperforms the baseline model.<\/jats:p>","DOI":"10.3233\/jifs-224532","type":"journal-article","created":{"date-parts":[[2023,5,26]],"date-time":"2023-05-26T13:19:47Z","timestamp":1685107187000},"page":"2579-2591","source":"Crossref","is-referenced-by-count":6,"title":["Research on dual-channel user portrait construction method based on DPCNN-BiGRU and attention mechanism"],"prefix":"10.1177","volume":"45","author":[{"given":"Hongyong","family":"Leng","sequence":"first","affiliation":[{"name":"School of Software, XinJiang University, Urumqi, China"},{"name":"School of Computer Science & Technology, Beijing Institute of Technology, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinxin","family":"Shao","sequence":"additional","affiliation":[{"name":"School of Software, XinJiang University, Urumqi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhe","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Software, XinJiang University, Urumqi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yurong","family":"Qian","sequence":"additional","affiliation":[{"name":"School of Software, XinJiang University, Urumqi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengnan","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Software, XinJiang University, Urumqi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zichen","family":"Li","sequence":"additional","affiliation":[{"name":"Big Data and Artificial Intelligence Academy, Guangdong Water Conservancy and Electricity Vocational and Technical College, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-224532_ref1","unstructured":"Alan C. , The road of interaction design [m], Beijing: Electronic Industry Press, (2006), 115\u2013135."},{"key":"10.3233\/JIFS-224532_ref2","first-page":"46","article-title":"Research on the construction of ecommerce user profile based on big data [j]","volume":"01","author":"Gang","year":"2019","journal-title":"E-commerce"},{"key":"10.3233\/JIFS-224532_ref3","doi-asserted-by":"crossref","unstructured":"Zigoris Philip and Zhang Yi , Bayesian adaptive user profiling with explicit andimplicit feedback[j]. In Proceedings of the 15th ACM International Conference onInformation and Knowledge Management (CIKM page 2006), (2006), 397\u2013404.","DOI":"10.1145\/1183614.1183672"},{"key":"10.3233\/JIFS-224532_ref4","unstructured":"Bradley Thomas A. and Carlin P. , Louis.bayes and empirical bayesmethods for data analysis[m]. Bayes and Empirical Bayes methods fordata analysis. ChapmanHall\/CRC, 1998."},{"key":"10.3233\/JIFS-224532_ref5","first-page":"37","article-title":"Early warning and prediction of ecommerce user loss [j]","volume":"9","author":"Yiqun","year":"2016","journal-title":"Systems Engineering"},{"key":"10.3233\/JIFS-224532_ref6","first-page":"8","article-title":"Combining data mining and machine learning for effective user profiling","volume":"96","author":"Fawcett","year":"1996","journal-title":"In KDD"},{"key":"10.3233\/JIFS-224532_ref7","doi-asserted-by":"crossref","unstructured":"Tuzhilin A. and Adomavicius G. , User profiling in personalization applications through rule discovery and validation[j]. Proceedings of the 5th International Conference on Data Miningand Knowledge Discovery. New York ACM Press (1999), 377\u2013381.","DOI":"10.1145\/312129.312287"},{"issue":"3","key":"10.3233\/JIFS-224532_ref8","first-page":"358","article-title":"Classification and regression trees(cart)[j]","volume":"40","author":"Olshen","year":"1984","journal-title":"Biometrics"},{"issue":"7","key":"10.3233\/JIFS-224532_ref9","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1080\/08839510600779688","article-title":"Apriori-sdadapting association rule learning to subgroup discovery[j]","volume":"20","author":"Lavrac","year":"2006","journal-title":"Applied Artificial Intelligence"},{"key":"10.3233\/JIFS-224532_ref10","doi-asserted-by":"crossref","unstructured":"Sugiyama Kazunari , Hatano Kenji and Yoshikawa Masatoshi , Adaptive web search based on user profile constructed without any effort from users. In Proceedings of the 13th international conference on World Wide Web, (2004), 675\u2013684.","DOI":"10.1145\/988672.988764"},{"key":"10.3233\/JIFS-224532_ref11","unstructured":"Microblog User Interest Modeling Based on FeaturePropagation[C]. Liu q,niu k,he z, et al. 2013 6th International Symposium on Computational Intelligenceand Design(ISCID). IEEE Computer Society, 2013."},{"key":"10.3233\/JIFS-224532_ref12","unstructured":"Croft W.B. and Wei X. , Lda-based document models for ad-hoc retrieval[c]. SIGIR 2006. Proceedings of the 29th Annual International ACM SIGIR Conferenceon Research and Development in Information Retrieval, Seattle, Washington, USA, August 6-11, ACM, 2006."},{"key":"10.3233\/JIFS-224532_ref13","doi-asserted-by":"crossref","unstructured":"Rahimi Afshin , Vu Duy , Cohn Trevor and Baldwin Timothy , Exploiting text and network context for geolocation of social media users. arXiv preprint arXiv:1506.04803, 2015.","DOI":"10.3115\/v1\/N15-1153"},{"key":"10.3233\/JIFS-224532_ref14","doi-asserted-by":"crossref","unstructured":"Miller Zachary , Dickinson Brian and Hu Wei , Gender prediction on twitter using stream algorithms with n-gram character features, 2012.","DOI":"10.4236\/ijis.2012.224019"},{"key":"10.3233\/JIFS-224532_ref15","unstructured":"Xianbo Zhao , User profile method based on multi-source weighted fusion [d]. Xi\u2019an Engineering University, 2021."},{"issue":"4","key":"10.3233\/JIFS-224532_ref16","first-page":"326","article-title":"bartle.gender classification with deep learning[j]","volume":"26","author":"Aric","year":"2015","journal-title":"Artificial Intelligence"},{"key":"10.3233\/JIFS-224532_ref17","doi-asserted-by":"crossref","unstructured":"Cao J. , Wang R. , Li Z. et al. Convolutional recurrent neural networksfor text classification[c]. 2019 International Joint Conference on Neural Networks (IJCNN), 2019.","DOI":"10.1109\/IJCNN.2019.8852406"},{"key":"10.3233\/JIFS-224532_ref18","first-page":"4171","article-title":"Bertpre-training of deep bidirectional rransformers for language understanding[c]","author":"Lee","year":"2019","journal-title":"Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics"},{"key":"10.3233\/JIFS-224532_ref19","first-page":"48","article-title":"Research on clustering algorithm[j]","volume":"191","author":"Lianyu","year":"2008","journal-title":"Journal of Software"},{"key":"10.3233\/JIFS-224532_ref20","first-page":"2826","article-title":"Zeus at hasoc: Hate speech detection based on albert-dpcnn[j]","author":"Li","year":"2020","journal-title":"CEUR Workshop Proceedings"},{"key":"10.3233\/JIFS-224532_ref21","unstructured":"Computation Neural Computation; Investigators from Xi\u2019an Jiao Tong University Release New Data on Neural Computation. Improving text classification with weighted word embeddings via a multi-channel textcnn model) [j], Journal of Robotics Machine Learning, 2019."},{"key":"10.3233\/JIFS-224532_ref22","first-page":"2021","article-title":"Interpretation of electrocardiogram heartbeat by cnn and gru[j]","author":"Xu","year":"2021","journal-title":"Computational and Mathematical Methods in Medicine"},{"key":"10.3233\/JIFS-224532_ref23","doi-asserted-by":"crossref","unstructured":"Harish B. , Kathpal N. and Baird Colin , The structure and energetics of low-lying states of rco and rnn free radicals[j], Canadian Journal of Chemistry 55(5) (1977).","DOI":"10.1139\/v77-120"},{"key":"10.3233\/JIFS-224532_ref24","first-page":"235","article-title":"Contextual sentiment embeddings via bi-directional gru language model[j]","author":"Liang-Chih","year":"2022","journal-title":"Knowledge-Based Systems"},{"key":"10.3233\/JIFS-224532_ref25","first-page":"3558","article-title":"Text emotion classification model based on bigru-attention neural network [j]","volume":"12","author":"Qingjie","year":"2019","journal-title":"Computer Application Research"},{"key":"10.3233\/JIFS-224532_ref26","unstructured":"Sogou user profile Mining CCF Competition data set in big data Precision Marketing. [22] https:\/\/www.datafountain.cn\/competitions\/239."},{"key":"10.3233\/JIFS-224532_ref28","doi-asserted-by":"crossref","unstructured":"Jingjing Yuan Yanqin Wu Le Zhang , Tiantian Lv and Ying Wang , Prediction and application of network business traffic based on lstm[j], Journal of Physics: Conference Series 2289(1), 2022.","DOI":"10.1088\/1742-6596\/2289\/1\/012011"},{"key":"10.3233\/JIFS-224532_ref29","unstructured":"Information Technology Medical Informatics; Researchers from University of Arizona Provide Details of New Studies and Findings in the Area of Medical Informatics. mining ecigarette adverse events in social media using bilstm recurrent neural network with word embedding representation [j], Network Weekly News, 2017."},{"key":"10.3233\/JIFS-224532_ref30","first-page":"2826","article-title":"Fake news detection in the urdu language using charcnn-roberta[j]","author":"Jiang","year":"2022","journal-title":"CEUR Workshop Proceedings"},{"key":"10.3233\/JIFS-224532_ref31","unstructured":"Bojanowski P. , Joulin A. , Grave E. et al. Bag of tricks for efficient text classification[c]. Proceedings of the15th Conference of the European Chapter of the association for Computational Linguistics: Volume 2, Short Papers. Valencia: Association for Computational Linguistics, (2017), pages 427\u2013431."},{"key":"10.3233\/JIFS-224532_ref32","unstructured":"Velikovi Petar , Cucurull G. , Casanova A. , Romero A. , Lio P. and Bengio Y. , Graph attention networks, 2017."}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-224532","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:46:07Z","timestamp":1777455967000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-224532"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,1]]},"references-count":31,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.3233\/jifs-224532","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,1]]}}}