{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T04:45:22Z","timestamp":1761108322372,"version":"3.37.3"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2019,2,26]],"date-time":"2019-02-26T00:00:00Z","timestamp":1551139200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Gusu Innovation Talent Foundation of Suzhou","award":["ZXT2017002"],"award-info":[{"award-number":["ZXT2017002"]}]},{"name":"National Key R&D Program of China","award":["2017YFC08219"],"award-info":[{"award-number":["2017YFC08219"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2019,12]]},"DOI":"10.1007\/s13042-019-00942-5","type":"journal-article","created":{"date-parts":[[2019,2,26]],"date-time":"2019-02-26T16:22:34Z","timestamp":1551198154000},"page":"3521-3537","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Word-character attention model for Chinese text classification"],"prefix":"10.1007","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3834-0580","authenticated-orcid":false,"given":"Xue","family":"Qiao","sequence":"first","affiliation":[]},{"given":"Chen","family":"Peng","sequence":"additional","affiliation":[]},{"given":"Zhen","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Yanfeng","family":"Hu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,2,26]]},"reference":[{"key":"942_CR1","unstructured":"Pratama BY, Sarno R (2016) Personality classification based on Twitter text using Naive Bayes, KNN and SVM. In: IEEE international conference on data and software engineering, pp\u00a0170\u2013174"},{"key":"942_CR2","unstructured":"Wandabwa H, Zhang D, Sammy K (2017) Text categorization via attribute distance weighted k-nearest neighbor classification. In: IEEE international conference on information technology, pp\u00a0225\u2013228"},{"key":"942_CR3","unstructured":"Steyn C, Waal AD (2017) Semi-supervised machine learning for textual anomaly detection. In: IEEE pattern recognition association of South Africa and robotics and mechatronics international conference, pp\u00a01\u20135"},{"issue":"3","key":"942_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10115-016-0924-1","volume":"49","author":"M Haddoud","year":"2016","unstructured":"Haddoud M, Mokhtari A, Lecroq T et al (2016) Combining supervised term-weighting metrics for svm text classification with extended term representation. Knowl Inf Syst 49(3):1\u201323","journal-title":"Knowl Inf Syst"},{"key":"942_CR5","unstructured":"Tuteja SK, Bogiri N (2017) Email spam filtering using BPNN classification algorithm. In: IEEE international conference on automatic control and dynamic optimization techniques, pp\u00a0915\u2013919"},{"key":"942_CR6","unstructured":"Sun RH, Hao J (2017) Comparisons of word representations for convolutional neural network: an exploratory study on tourism Weibo classification. In: IEEE international conference on service systems and service management, pp\u00a01\u20135"},{"issue":"C","key":"942_CR7","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.knosys.2016.05.045","volume":"106","author":"J Li","year":"2016","unstructured":"Li J, Li J, Fu X et al (2016) Learning distributed word representation with multi-contextual mixed embedding. Knowl Based Syst 106(C):220\u2013230","journal-title":"Knowl Based Syst"},{"key":"942_CR8","unstructured":"Cheng J, Li P, Ding Z et al (2017) Sentiment classification of chinese microblogging texts with global RNN. In: IEEE international conference on data science in cyberspace, pp\u00a0653\u2013657"},{"key":"942_CR9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TVCG.2016.2598432","volume":"99","author":"S Liu","year":"2017","unstructured":"Liu S, Bremer PT, Thiagarajan JJ et al (2017) Visual exploration of semantic relationships in neural word embeddings. IEEE Trans Vis Comput Graph 99:1\u20131","journal-title":"IEEE Trans Vis Comput Graph"},{"key":"942_CR10","unstructured":"Zhang L, Chen C (2017) Sentiment classification with convolutional neural networks: an experimental study on a large-scale chinese conversation corpus. In: IEEE international conference on computational intelligence and security, pp\u00a0165\u2013169"},{"key":"942_CR11","doi-asserted-by":"crossref","unstructured":"Zhuang H, Wang C, Li C et al (2017) Natural language processing service based on stroke-level convolutional networks for Chinese text classification. In: IEEE international conference on web services, pp\u00a0404\u2013411","DOI":"10.1109\/ICWS.2017.46"},{"key":"942_CR12","unstructured":"Chen X, Xu L, Liu Z et al (2015) Joint learning of character and word embeddings. In: International conference on artificial intelligence, pp\u00a01236\u20131242"},{"key":"942_CR13","doi-asserted-by":"crossref","unstructured":"Lai S, Xu L, Liu K, Zhao (2015) Recurrent convolutional neural networks for text classification. In: AAAI, pp\u00a02267\u20132273","DOI":"10.1609\/aaai.v29i1.9513"},{"issue":"11","key":"942_CR14","doi-asserted-by":"publisher","first-page":"113","DOI":"10.3390\/fi10110113","volume":"10","author":"Y Li","year":"2018","unstructured":"Li Y, Wang X, Xu P (2018) Chinese text classification model based on deep learning. Future Internet 10(11):113","journal-title":"Future Internet"},{"key":"942_CR15","unstructured":"Yang J, Lyu Q, Gao S et al (2017) Review aspect extraction based on character-enhanced embedding models. In: IEEE international conference on network infrastructure and digital content, pp\u00a0219\u2013223"},{"key":"942_CR16","unstructured":"Zhang X, Zhao J, Lecun Y (2015) Character-level convolutional networks for text classification. In: Advances in neural information processing systems, pp\u00a0649\u2013657"},{"issue":"4","key":"942_CR17","first-page":"759","volume":"21","author":"Y Zhou","year":"2017","unstructured":"Zhou Y, Xu J, Cao J et al (2017) Hybrid attention networks for Chinese short text classification. Computaci\u00f3n y Sistemas 21(4):759\u2013769","journal-title":"Computaci\u00f3n y Sistemas"},{"key":"942_CR18","doi-asserted-by":"crossref","unstructured":"Cho K, Van Merrienboer B, Gulcehre C et al (2014) Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv:1406.1078","DOI":"10.3115\/v1\/D14-1179"},{"key":"942_CR19","doi-asserted-by":"crossref","unstructured":"Bafna P, Pramod D, Vaidya A (2016) Document clustering: TF-IDF approach. In: IEEE international conference on electrical, electronics, and optimization techniques, pp\u00a061\u201366","DOI":"10.1109\/ICEEOT.2016.7754750"},{"key":"942_CR20","doi-asserted-by":"crossref","unstructured":"Qu Z, Song X, Zheng S, Wang X, Song X, Li Z (2018) Improved Bayes method based on TF-IDF feature and grade factor feature for chinese information classification. In: 2018 IEEE international conference on big data and smart computing, pp\u00a0677\u2013680","DOI":"10.1109\/BigComp.2018.00124"},{"key":"942_CR21","unstructured":"Le QV, Mikolov T (2014) Distributed representations of sentences and documents. In: International conference on machine learning, pp\u00a01188\u20131196"},{"key":"942_CR22","unstructured":"Socher R, Huval B, Manning CD, Ng AY (2012) Semantic compositionality through recursive matrix-vector spaces. In: The 2012 joint conference on empirical methods in natural language processing and computational natural language learning, pp\u00a01201\u20131211"},{"key":"942_CR23","unstructured":"Pengfei Liu X, Qiu X, Chen S, Wu XH (2015) Multi-timescale long short-term memory neural network for modelling sentences and documents. In: The 2015 conference on empirical methods in natural language processing, pp\u00a02326\u20132335"},{"key":"942_CR24","doi-asserted-by":"crossref","unstructured":"Kalchbrenner N, Grefenstette E, Blunsom P (2014) A convolutional neural network for modelling sentences. In: Proceedings of the 52nd ACL, pp\u00a0655\u2013665","DOI":"10.3115\/v1\/P14-1062"},{"key":"942_CR25","doi-asserted-by":"crossref","unstructured":"Kim Y (2014) Convolutional neural networks for sentence classification. In: Proceedings of the 2014 conference on EMNLP, pp\u00a01746\u20131751","DOI":"10.3115\/v1\/D14-1181"},{"key":"942_CR26","unstructured":"Yang Z, Yang D, Dyer C et al (2017) Hierarchical attention networks for document classification. In: Conference of the North American chapter of the association for computational linguistics: human language technologies, pp\u00a01480\u20131489"},{"key":"942_CR27","doi-asserted-by":"crossref","unstructured":"Li Y, Li W, Sun F, Li S (2015) Component-enhanced chinese character embeddings. In: Proceedings of the 2015 conference on EMNLP, pp\u00a0829\u2013834","DOI":"10.18653\/v1\/D15-1098"},{"key":"942_CR28","unstructured":"Zhou Y, Xu B, Xu J et al (2017) Compositional recurrent neural networks for chinese short text classification. In: IEEE international conference on web intelligence, pp\u00a0137\u2013144"},{"key":"942_CR29","unstructured":"Gao S, Ramanathan A, Tourassi G (2017) Hierarchical convolutional attention networks for text classification. In: The 3rd workshop on representation learning for NLP, pp\u00a011\u201323"},{"issue":"3","key":"942_CR30","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1109\/TASLP.2018.2789721","volume":"26","author":"J Su","year":"2018","unstructured":"Su J, Zeng J, Xiong D et al (2018) A hierarchy-to-sequence attentional neural machine translation model. IEEE\/ACM Trans Audio Speech Lang Process 26(3):623\u2013632","journal-title":"IEEE\/ACM Trans Audio Speech Lang Process"},{"issue":"9","key":"942_CR31","doi-asserted-by":"publisher","first-page":"2045","DOI":"10.1109\/TMM.2017.2729019","volume":"19","author":"L Gao","year":"2017","unstructured":"Gao L, Guo Z, Zhang H et al (2017) Video captioning with attention-based lstm and semantic consistency. IEEE Trans Multimed 19(9):2045\u20132055","journal-title":"IEEE Trans Multimed"},{"key":"942_CR32","doi-asserted-by":"crossref","unstructured":"Yang Z, He X, Gao J et al (2016) Stacked attention networks for image question answering. In: IEEE conference on computer vision and pattern recognition, pp\u00a021\u201329","DOI":"10.1109\/CVPR.2016.10"},{"key":"942_CR33","doi-asserted-by":"crossref","unstructured":"Zhou P, Shi W, Tian J et al (2016) Attention-based bidirectional long short-term memory networks for relation classification. In: Meeting of the association for computational linguistics, pp\u00a0207\u2013212","DOI":"10.18653\/v1\/P16-2034"},{"key":"942_CR34","doi-asserted-by":"crossref","unstructured":"Wang L, Cao Z, Melo GD et al (2016) Relation classification via multi-level attention CNNs. In: Meeting of the association for computational linguistics, pp\u00a01298\u20131307","DOI":"10.18653\/v1\/P16-1123"},{"key":"942_CR35","doi-asserted-by":"crossref","unstructured":"Ling Y, An Y, Liu M et al (2017) Integrating extra knowledge into word embedding models for biomedical NLP tasks. In: IEEE international joint conference on neural networks, pp\u00a0968\u2013975","DOI":"10.1109\/IJCNN.2017.7965957"},{"issue":"3","key":"942_CR36","first-page":"625","volume":"11","author":"D Erhan","year":"2010","unstructured":"Erhan D, Bengio Y, Courville A et al (2010) Why does unsupervised pre-training help deep learning. J Mach Learn Res 11(3):625\u2013660","journal-title":"J Mach Learn Res"},{"key":"942_CR37","doi-asserted-by":"crossref","unstructured":"Wang Q, Xu J, Chen H et al (2017) Two improved continuous bag-of-word models. In: IEEE international joint conference on neural networks, pp\u00a02851\u20132856","DOI":"10.1109\/IJCNN.2017.7966208"},{"key":"942_CR38","first-page":"1","volume":"2","author":"J Wang","year":"2017","unstructured":"Wang J, Liu F, Qin S (2017) Global exponential stability of uncertain memristor-based recurrent neural networks with mixed time delays. Int J Mach Learn Cybern 2:1\u201313","journal-title":"Int J Mach Learn Cybern"},{"issue":"1","key":"942_CR39","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1007\/s13042-012-0077-9","volume":"4","author":"F Na Liu","year":"2013","unstructured":"Na Liu F, Chen M, Lu (2013) Spectral co-clustering documents and words using fuzzy K-harmonic means. Int J Mach Learn Cybern 4(1):75\u201383","journal-title":"Int J Mach Learn Cybern"},{"issue":"2","key":"942_CR40","first-page":"9","volume":"4","author":"P Li","year":"2016","unstructured":"Li P, Yan Ye (2016) Chinese spam filtering based on back-propagation neural networks. Softw Eng 4(2):9\u201312","journal-title":"Softw Eng"},{"key":"942_CR41","unstructured":"Sang L, Xie F, Liu X et al (2017) WEFEST: word embedding feature extension for short text classification. In: IEEE international conference on data mining workshops, pp\u00a0677\u2013683"},{"issue":"1","key":"942_CR42","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1007\/s13042-012-0068-x","volume":"4","author":"AB Musa","year":"2013","unstructured":"Musa AB (2013) Comparative study on classification performance between support vector machine and logistic regression. Int J Mach Learn Cybern 4(1):13\u201324","journal-title":"Int J Mach Learn Cybern"},{"key":"942_CR43","unstructured":"Mikolov T, Sutskever I, Chen K, Corrado G, Dean J (2013) Distributed representations of words and phrases and their compositionality. In: Advances in neural information processing systems, pp\u00a03111\u20133119"},{"key":"942_CR44","unstructured":"Zhang D, Wang D (2015) Relation classification via recurrent neural network. Comput Sci. arXiv:1508.01006"},{"issue":"5","key":"942_CR45","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1016\/j.neunet.2005.06.042","volume":"18","author":"A Graves","year":"2005","unstructured":"Graves A, J\u00fcrgen Schmidhuber (2005) Framewise phoneme classification with bidirectional lstm and other neural network architectures. Neural Netw 18(5):602\u2013610","journal-title":"Neural Netw"},{"key":"942_CR46","unstructured":"Yong Z, Meng JE, Venkatesan R et al (2016) Sentiment classification using comprehensive attention recurrent models. In: IEEE international joint conference on neural networks, pp\u00a01562\u20131569"},{"key":"942_CR47","doi-asserted-by":"crossref","unstructured":"Luong MT, Pham H, Manning CD (2015) Effective approaches to attention-based neural machine translation. In: Conference on empirical methods in natural language processing, pp\u00a01412\u20131421","DOI":"10.18653\/v1\/D15-1166"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13042-019-00942-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-00942-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-019-00942-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,12]],"date-time":"2022-09-12T17:24:05Z","timestamp":1663003445000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13042-019-00942-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,2,26]]},"references-count":47,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2019,12]]}},"alternative-id":["942"],"URL":"https:\/\/doi.org\/10.1007\/s13042-019-00942-5","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2019,2,26]]},"assertion":[{"value":"12 September 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 February 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 February 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}