Abstract
In regions of visual inference, optimized performance is demonstrated by capsule networks on structured data. Classification of hierarchical multi-label text is performed with a simple capsule network algorithm in this paper. It is further compared to support vector machine (SVM), Long Short Term Memory (LSTM), artificial neural network (ANN), convolutional Neural Network (CNN) and other neural and non-neural network architectures to demonstrate its superior performance. The Blurb Genre Collection (BGC) and Web of Science (WOS) datasets are used for experimental purpose. The encoded latent data is combined with the algorithm while handling structurally diverse categories and rare events in hierarchical multi-label text applications.
References
- Ren, H., & Lu, H. (2018). Compositional coding capsule network with k-means routing for text classification. arXiv preprint arXiv:1810.09177.
- DiviyaPrabha, V., & Rathipriya, R. (2020). Sentimental Analysis using Capsule Network with Gravitational Search Algorithm. Journal of Web Engineering, 762-778.
- Yang, M., Zhao, W., Chen, L., Qu, Q., Zhao, Z., & Shen, Y. (2019). Investigating the transferring capability of capsule networks for text classification. Neural Networks, 118, 247-261.
- Wu, Y., Li, J., Chen, V., Chang, J., Ding, Z., & Wang, Z. (2020, July). Text Classification using Triplet Capsule Networks. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-7). IEEE.
- Xiao, L., Zhang, H., Chen, W., Wang, Y., & Jin, Y. (2018). MCapsNet: Capsule network for text with multi-task learning. In Proceedings of the 2018 conference on empirical methods in natural language processing (pp. 4565-4574).
- Jain, D. K., Jain, R., Upadhyay, Y., Kathuria, A., & Lan, X. (2020). Deep Refinement: capsule network with attention mechanism-based system for text classification. Neural Computing and Applications, 32(7), 1839-1856.
- Chen, B., Huang, X., Xiao, L., & Jing, L. (2020, July). Hyperbolic Capsule Networks for Multi-Label Classification. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 3115-3124).
- Jacob, I. J. (2020). Performance evaluation of caps-net based multitask learning architecture for text classification. Journal of Artificial Intelligence, 2(01), 1-10.
- Zhang, K., Jiao, M., Chen, X., Wang, Z., Liu, B., & Liu, L. (2019). SC-BiCapsNet: A sentiment classification model based on Bi-channel capsule network. IEEE Access, 7, 171801-171813.
- Lei, K., Fu, Q., Yang, M., & Liang, Y. (2020). Tag recommendation by text classification with attention-based capsule network. Neurocomputing, 391, 65-73.
- Peng, H., Li, J., Wang, S., Wang, L., Gong, Q., Yang, R., ... & He, L. (2019). Hierarchical taxonomy-aware and attentional graph capsule RCNNs for large-scale multi-label text classification. IEEE Transactions on Knowledge and Data Engineering.
- Zhao, W., Ye, J., Yang, M., Lei, Z., Zhang, S., & Zhao, Z. (2018). Investigating capsule networks with dynamic routing for text classification. arXiv preprint arXiv:1804.00538.
- Vijayakumar, T., & Vinothkanna, R. (2020). Capsule Network on Font Style Classification. Journal of Artificial Intelligence, 2(02), 64-76.
- Vijayakumar, T. (2019). Comparative study of capsule neural network in various applications. Journal of Artificial Intelligence, 1(01), 19-27.