Abstract
Cellular neural network is one of the classic neural networks. This paper designs a one-dimensional pairwise CNN, and then develops a global alignment algorithm for the Chinese texts using this CNN. The method mainly includes these processing steps, namely the initialization of the CNN, the generation of the alignment path, and the global alignment of the texts in accordance with the comments. The experiments show that the developed method is efficient, and compared to the other three methods, it could obtain the alignment result of two Chinese texts with the higher similarity and the less time.
This work is supported by the National Science Foundation of China (NSFC) under the Grant number 61175061.
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References
Yu, X., Jianxun, L., Mingdong, T., Yiping, W.: Empirical Study of Chinese Text Similarity Computation Based on Machine Translation. In: Proceedings of the Seventh International Conference on Semantics Knowledge and Grid (SKG 2011), pp. 156–159 (2011)
Fan, X., Qiaoming, Z., Peifeng, L.: Detecting Text Similarity over Chinese Research Papers Using MapReduce. In: Proceedings of 2011 12th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2011), pp. 197–202 (2011)
Xiuhong, W., Shiguang, J., Shengli, W.: Challenges in Chinese Text Similarity Research. In: Proceedings of 2008 International Symposiums on Information Processing (ISIP 2008), pp. 297–302 (2008)
Xiangdong, L., Hangyu, L., Han, J., Huang, L.: Research on the categorization accuracy of different similarity measures on Chinese texts. In: Proceedings of 2011 International Conference on Business Management and Electronic Information (BMEI 2011), vol. 4, pp. 224–227 (2011)
McAllister, S.R., Rajgaria, R., Floudas, C.A.: Global pairwise sequence alignment through mixed-integer linear programming: a template-free approach. Optimization Methods and Software 22(1), 127–144 (2007)
Shiyi, S., Jun, Y., Adam, Y., Pei, H.: Super Pairwise Alignment (SPA): An Effecient Approach to Global Alignment for Homologous Sequences. Journal of Computational Biology 9(3), 77–486 (2002)
Pak, C.W., Kwong-kwok, W., Harlan, F., Jim, T.: Global visualization and alignments of whole bacterial genomes. IEEE Transactions on Visualization and Computer Graphics 9(3), 361–377 (2003)
Wu, S., Wu, Y.: Chinese and English Word Similarity Measure Based on Chinese WordNet. Journal of zhengzhou university (Natural Science Edition) 2, 66–69 (2010)
Ke, Z., Jun, L., Xilin, C.: Text similarity computing based on sememe Vector Space. In: Proceedings of 2013 4th IEEE International Conference on Software Engineering and Service Science (ICSESS 2013), pp. 208–211 (2013)
Metin, S.K., Kisla, T., Karaoglan, B.: Text similarity analysis using IR lists. In: Proceedings of Signal Processing and Communications Applications Conference (SIU 2013), pp. 1–4 (2013)
Chua, L.O., Yang, L.: Cellular neural networks: Theory. IEEE Trans. on Circuits and Systems 35, 1257–1272 (1988)
Yonggui, K., Cunchen, G.: Global exponential stability analysis for cellular neural networks with variable coefficients and delays. Neural Computing and Applications 17(3), 291–295 (2008)
Guowei, Y., Yonggui, K., Wei, L., Xiqian, S.: Exponential stability of impulsive stochastic fuzzy cellular neural networks with mixed delays and reaction Cdiffusion terms. Neural Computing and Applications 23(3-4), 1109–1121 (2013)
Amanatidis, D., Tsaptsinos, D., Giaccone, P., Jones, G.: Optimizing motion and colour segmented images with neural networks. Neurocomputing 62, 197–223 (2004)
Shukai, D., Xiaofang, H., Lidan, W., Shiyong, G.: Hybrid memristor/RTD structure-based cellular neural networks with applications in image processing. Neural Computing and Applications 25(2), 291–296 (2014)
Yangtao, L., Di, X., Huaqin, L., Shaojiang, D.: Parallel chaotic Hash function construction based on cellular neural network. Neural Computing and Applications 21(7), 1563–1573 (2012)
Manganaro, G., Gyvez, G.P.: One-dimensional discrete-time CNN with multiplexed template-hardware. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 5, 764–769 (2000)
Takahashi, N., Nagayoshi, M., Kawabata, S., Nishi, T.: Stable Patterns Realized by a Class of One-Dimensional Two-Layer CNNs. IEEE Trans. on Circuits and Systems: Regular Papers 11, 3607–3620 (2008)
Jun, W., Peter, D.K., Toby, J.: MCALIGN2: Faster, accurate global pairwise alignment of non-coding DNA sequences based on explicit models of indel evolution. BMC Bioinformatics 7, 292 (2006)
Zhao-hui, Q., Xiao-Qin, Q., Chen-chen, L.: New method for global alignment of 2DNA sequences by the tree data structure. Journal of Theoretical Biology 263, 227–236 (2010)
Guillaume, R., Dominique, L.: GASSST: global alignment short sequence search tool. Bioinformatics 26(20), 2534–2540 (2010)
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Ji, L., Pu, X., Liu, G. (2015). Chinese Text Similarity Computation via the 1D-PW CNN. In: Handa, H., Ishibuchi, H., Ong, YS., Tan, K. (eds) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Volume 1. Proceedings in Adaptation, Learning and Optimization, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-13359-1_19
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DOI: https://doi.org/10.1007/978-3-319-13359-1_19
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