基于时间序列的人工智能在线翻译网络分析
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作者单位:

1.三江学院外国语学院,南京 210012;2.南京宇天万维信息技术有限公司,南京 210019;3.厦门大学信息学院,厦门 361005

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国家自然科学基金(61971362)资助项目;江苏省社会科学基金(19YYB003)资助项目。


Network Analysis of Artificial Intelligence Online Translation Based on Time Series
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Affiliation:

1.School of Foreign Languages, Sanjiang University, Nanjing 210012, China;2.Nanjing Yutian Wanwei Information Technology Co Ltd, Nanjing 210019, China;3.School of Informatics, Xiamen University, Xiamen 361005, China

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    摘要:

    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。

    Abstract:

    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.

    图1 最短路径长度的分布Fig.1 Distribution of the shortest path length
    图2 在线翻译网络社团结构Fig.2 Community structure of the online translation network
    图3 4种引领模式的分布特征Fig.3 Distribution characteristics of four leading modes
    表 1 网络节点的拓扑性质Table 1 Topological properties of network nodes
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冯吉芳,田德红,孙海信.基于时间序列的人工智能在线翻译网络分析[J].数据采集与处理,2021,36(2):296-303

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  • 收稿日期:2020-10-10
  • 最后修改日期:2021-01-10
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  • 在线发布日期: 2021-04-15