Neural Networks in Semantic Analysis
2020
Abstract
This paper presents research of the possibilities of application deep neural networks in semantic analysis. This paper presents the current situation in this area and the prospects for application an artificial intelligence in semantic analysis and trend and tendencies of this science area. For better understanding future tendencies of researches in semantical area we present detailed review of the studies in semantic analysis with using artificial intelligence, studies about a human brain. Keywords-Semantic Analysis, Deep Neural Networks, Forecasting, Processing of Natural Language. Нейронные сети в семантическом анализе Аверкин А.Н. Ярушев С.А. В статье описываются глубинные архитектуры искусственных нейронных сетей и возможности их применения в семантическом анализе. Рассматривается история разработки глубинных нейронных сетей. Исследуются современные тенденции в задачах семантического анализа, а также представляется кратких обзор исследований в данной области.
References (13)
- Ranzato, M. A., & Szummer, M.: Semi-supervised learning of compact document representations with deep networks. In: Proceedings of the 25th international conference on Machine learning. pp. 792-799, ACM, 2008.
- Hinton, Geoffrey E., Simon Osindero, and Yee-Whye: "A fast learning algorithm for deep belief nets." Neural computation 18.7: pp. 1527-1554, 2012.
- Deep Learning: Microsoft's Richard Rashid demos deep learning for speech recognition in China, http://deeplearning.net/2012/12/13/microsofts-richard-rashid- demos-deep-learning-for-speech-recognition-in-china/, last accessed 2020/01/17
- Yu B., Xu Z., Li C.: Latent semantic analysis for text categoriza- tion using neural network. //Knowledge-Based Systems, . 21, №. 8, pp. 900-904, 2008.
- Mountcastle V.: The columnar organization of neocortex // Brain, vol. 120, P. 701-722, 1997.
- Kohonen T.: Self-Organizing Maps. Springer Verlag, 2001.
- Hinaut X. et al.: A Recurrent Neural Network for Multiple Lan- guage Acquisition: Starting with English and French //CoCo@ NIPS, 2015.
- Miikkulainen, R.: Subsymbolic case-role analysis of sentences with embedded clauses. Cognitive Sci 20: pp. 47-73, 1996.
- Hinaut X., Dominey P. F.: Real-time parallel processing of grammatical structure in the fronto-striatal system: a recurrent network simulation study using reservoir computing //PloS one, .8, №. 2, p. 52946, 2013.
- Frank, S. L.: (2006). Strong systematicity in sentence processing by an Echo State Network. In Proc. of ICANN, pp. 505-514, 2006.
- Peter Ford Dominey, Toshio Inui, Michel Hoen: Neural net- work processing of natural language: II. Towards a unified model of corticostriatal function in learning sentence compre- hension and non-linguistic sequencing // Brain and Language. doi:10.1016/j.bandl.2008.08.002, 2008.
- Caplan, D., Baker, C., Dehaut, F.: Syntactic determinants of sentence comprehension in aphasia. Cognition, 21, 117-175, 1985.
- Shumski, S.: Brain and language: Hypotheses about structure of a natural language, 2017.