基于三元组特征和词向量技术的中文专利侵权检测研究
发布时间：2018-08-03 11:27
【摘要】：针对中文专利侵权检测中关键词特征表达能力弱以及句子结构特征容易引起噪声干扰的问题,提出了一种通过抽取三元组特征来改进中文专利侵权检测的方法。该方法将专利权利要求书抽取为三元组特征的集合,并结合词向量技术和How Net计算三元组特征间的语义相似度,从而有效提高对疑似侵权专利的识别能力。实验结果表明,该方法取得了较好的检测效果,且在准确率上要高于其他方法。
[Abstract]:Aiming at the problem of weak expression of keyword features in Chinese patent infringement detection and noise interference caused by sentence structure features, this paper proposes a method to improve Chinese patent infringement detection by extracting triple features. In this method, the patent claim is extracted as a set of triple features, and the semantic similarity between the features of the triple is calculated by combining word vector technology and How Net, so as to improve the ability to identify the suspected patent infringement effectively. The experimental results show that this method has better detection effect and is more accurate than other methods.
【作者单位】： 江苏大学计算机科学与通信工程学院;南京审计大学工学院;
【基金】：国家自然科学基金资助项目(71271117) 江苏省六大人才高峰项目(2013-WLW-005) 江苏省自然科学基金资助项目(BK20150531)
【分类号】：G306;TP391.1
，
本文编号：2161603
[Abstract]:Aiming at the problem of weak expression of keyword features in Chinese patent infringement detection and noise interference caused by sentence structure features, this paper proposes a method to improve Chinese patent infringement detection by extracting triple features. In this method, the patent claim is extracted as a set of triple features, and the semantic similarity between the features of the triple is calculated by combining word vector technology and How Net, so as to improve the ability to identify the suspected patent infringement effectively. The experimental results show that this method has better detection effect and is more accurate than other methods.
【作者单位】： 江苏大学计算机科学与通信工程学院;南京审计大学工学院;
【基金】：国家自然科学基金资助项目(71271117) 江苏省六大人才高峰项目(2013-WLW-005) 江苏省自然科学基金资助项目(BK20150531)
【分类号】：G306;TP391.1
，
本文编号：2161603
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