The boom in wireless networking technology has led to an exponential increase in the number of web comments. Therefore, sentiment analysis of web comments is vital, and aspect-based sentiment analysis(ABSA) is very useful for the sentiment feature extraction of web comments. Currently, context-dependent sentiment feature typically derives from recurrent neural networks (RNN), and an average target vector usually replaces the target vector. However, web comments have become increasingly complex, and RNN may lose some essential sentiment information. At the same time, the average target vector may be the wrong target feature. We propose a new Transformer based memory network (TF-MN) to correct the shortcomings of the previous method. In TF-MN, the task becomes the question-answering process, which optimizes context, question, and the memory module. We use a global self-attention mechanism and a local attention mechanism (memory network) to construct emotionally inclined web comment semantics. Since self-attention can only obtain global semantic links, words such as nouns, prepositions, and adverbs still affect the emotional extraction of comments. To shield the influence of unrelated vocabulary on classification, we propose to use improved memory networks to optimize the extraction of web comments semantics. We conduct experiments on two datasets, and experimental results show that our model exceeds the state-of-the-art model.
The slope stability problems of combined open-pit with underground mining is such a key technology and the core problem of mining safety production. This paper apply the numerical simulation analysis on engineering project, and using Midas, FLAC3D and other software analysis the slope stability, slip deformation characteristics and follow trends of combined open-pit with underground mining mining systematically. Due to the impact of both the underground mining and open-pit mining, the surface subsidence curves is multiple sink basins of different sizes, so the rock slope deformation extent of different regions is different. We find that the damage of the overlying rock is different during the the exploitation stage, indicate that with different mining thickness has important influence of the damage of the overlying rock, so the slope stability evaluation requires a combination of the specific circumstances of the project to analysis and evaluation of exploitation.
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