期刊
FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY
卷 30, 期 10, 页码 -出版社
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0218348X2240268X
关键词
Machine Learning; Textual Data Analysis; Attention Mechanism; LSTM Network; Natural Language Processing
资金
- Municipal science and technology project of Shaoyang: With the Background of One belt, one road, translation study of Agricultural Technology English based on Multimodal Big Data Context Theory [2020GZ85]
- Project of Shaoyang Federation of Social Sciences: On the Background of One belt, one road, the Study and Dissemination of China's Classical Culture -Taking Ancient Poetry Image Translation Research as an example [21YBB35]
The creation of language models is crucial in natural language processing as it provides possible distributions in word sequences and unique representations for each word occurrence. An innovative neural network model with attention mechanism and coverage optimization is proposed to better align the output with the input sequence and offer helpful information.
The creation of language models is a vital object of natural language processing because it creates a possible distribution in a sequence of words and offers a unique representation of each occurrence of a word. Therefore, an intelligent language model can differentiate the subtle nuances of language and model its syntax and semantics. It also allows the acquisition of high-level representations. In addition, it serves as an initial model with helpful information, which can be transferred to various other word processing methods for a deeper and more complete understanding of the language. This work proposes an innovative Long Short-Term Memory (LSTM) neural network whose implementation is based on the use of an attention mechanism as a measure of alignment of the output with the input sequence and a corresponding coverage optimization mechanism. The optimization mechanism informs the model about the possible outcomes at each step which have already been produced in previous actions. The adaptation and evaluation of the system's design parameters were tested in multidimensional and challenging data sets We were considering parametric and heuristic procedures for finding the optimal combination of hyper-parameters. Experimental results demonstrate the quality of the proposed system, revealing essential directions for the design of similar systems.
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