Weakly-Supervised Hierarchical Text ClassificationEI
Hierarchical text classification, which aims to classify text documents into a given hierarchy, is an important task in many real-world applications. Recently, deep neural models are gaining increasing popularity for text classification due to their expressive power and minimum requirement for feature engineering. However, applying deep neural networks for hierarchical text classification remains challenging, because they heavily rely on a large amount of training data and meanwhile cannot easily determine appropriate levels of docume...更多
- 2Xingyuan Chen, Yunqing Xia, Peng Jin, John A. Carroll. Dataless Text Classification with Descriptive LDA.AAAI, pp. 2224-2231, 2015.
- 4Lijuan Cai, Thomas Hofmann. Hierarchical document categorization with support vector machines.CIKM, pp. 78-87, 2004.
- 8Dan Roth, Xin Li. Learning question classifiers., 2002.
- 9Evgeniy Gabrilovich, Shaul Markovitch. Computing semantic relatedness using Wikipedia-based explicit semantic analysis.IJCAI, pp. 1606-1611, 2007.
- 10Michelangelo Ceci, Donato Malerba. Classifying web documents in a hierarchy of categories: a comprehensive study.J. Intell. Inf. Syst., pp. 37-78, 2007.
- 11Arindam Banerjee, Inderjit S. Dhillon, Joydeep Ghosh, Suvrit Sra. Clustering on the Unit Hypersphere using von Mises-Fisher Distributions.Journal of Machine Learning Research, pp. 1345-1382, 2005.
- 13Kuzman Ganchev, João Graça, Jennifer Gillenwater, Ben Taskar. Posterior Regularization for Structured Latent Variable Models.Journal of Machine Learning Research, pp. 2001-2049, 2010.
- 14Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification.Annual Conference on Neural Information Processing Systems, pp. 649-657, 2015.
- 16Duyu Tang, Bing Qin, Ting Liu. Document Modeling with Gated Recurrent Neural Network for Sentiment Classification.Conference on Empirical Methods in Natural Language Processing, 2015.