摘要
【目的】为满足中文商标侵权判定过程中检测语义相似度的需求,提出一种改进的中文商标语义相似度计算方法。【方法】引入新参数改进传统的基于How Net的中文商标语义相似度计算方法,并收集大量商标数据作为相似度检测的支持数据以弥补How Net词库的局限,分别使用传统方法和改进后的方法对样本数据进行相似度检测,并对比准确率验证改进后方法的有效性。【结果】实验结果显示,改进后的方法比传统方法准确率更高、有更好的区分度。【局限】相似度检测支持数据——商标数据库中的数据量可以进一步丰富。【结论】改进后的中文商标语义相似度检测方法可以作为检测中文商标语义相似度的有效方法。
[Objective] This paper proposes a new method to determine the semantic similarity of Chinese trademarks, aiming to meet the demands of judging trademark infringements. [Methods] First, we modified the How Net based algorithm with new parameters to calculate the semantic similarity. Then, we retrieved a large number of trademark data to expand the coverage of How Net. Third, we compared the performance of traditional and improved methods with the sample data. [Results] The modified algorithm could yield better results. [Limitations] The supporting data for similarity detection, i.e. trademark database, needs to be expanded. [Conclusions] The proposed method could effectively detect the semantic similarity of Chinese trademarks.
出处
《数据分析与知识发现》
CSSCI
CSCD
2017年第11期19-28,共10页
Data Analysis and Knowledge Discovery
