基于时间序列的人工智能在线翻译网络分析

Network Analysis of Artificial Intelligence Online Translation Based on Time Series

从复杂网络角度出发,基于时间序列数据构建了人工智能在线翻译搜索指数的网络模型,并根据我国实际数据分析其网络结构特征。研究结果表明:在线翻译搜索指数虽然呈现出显著的波动特征,但大部分时间仍以小波动为主;在线翻译网络的最短路径长度分布近似呈偏态分布,网络中从一个符号到另一个符号的转换平均需要3个中间符号;波动性较小的符号具有较大的聚类系数;在线翻译整体呈下降趋势,经历了从早期不成熟到逐渐成熟的过程。

From the perspective of complex networks,this paper constructs a network model of the search index of artificial intelligence online translation based on the time series data,and then analyzes its structure characteristics based on actual data from China.The results show that:although the search index of online translation shows significant fluctuation characteristics,it is still dominated by small fluctuations in most of the time;the distribution of the shortest path lengths of the online translation network is approximately skewed distribution,and the conversion from one symbol to another in the network requires three intermediate symbols on average;the symbols with less volatility have larger clustering coefficient;online translation shows a downward trend as a whole,and has experienced a process from early immature to gradually mature.