Abstract: Patent contains lots of information about background, technology, function and so on, which plays an important role in innovation field. Patent is something created by innovation knowledge, at the same time, it promotes us to make more use of innovation knowledge and break the inherent thinking and the limitation of knowledge, which inspires designers in the process of product design. From the term of innovation design, a new method for extracting innovation knowledge was proposed based on combination feature and maximum entropy classifier. The natural language processing was used, patent terms recognition algorithm was given, and word feature and syntactic feature of the closed package tree in the shortest path were jointed to compute the middle result. After that, the maximum entropy algorithm was applied to extract innovation knowledge based on semantic analysis and mark the attributes of knowledge. The results show that the combination feature can effectively deal with patent issues which need to be solved, and the relationships among the semantic role of knowledge innovation about target function, function principle and position feature in the technical scheme.

Key words: semantic analysis, patent knowledge, innovation knowledge, information extraction, semantic role, maximum entropy

摘要： 专利蕴含丰富的背景、技术、功能等知识,对创新设计领域起着重要的作用。对创新知识进行有效提取,能推动人们对知识的利用,助于突破固有的思维定势及知识面的限制,启发设计者从独特、新颖的角度进行产品设计。从创新设计的角度,提出基于组合特征和最大熵分类器的专利创新知识抽取方法。该方法运用自然语言处理方法,增加专利领域术语识别算法,联合词特征和最短路径闭包树句法特征,最后采用最大熵进行基于语义分析的知识提取,并对知识属性进行标注。实验结果表明,引入组合特征,能高效地处理专利要解决的问题,以及技术方案中的目标功能、作用原理、位置特征等创新知识之间的语义角色关系。

关键词: 语义分析, 专利知识, 创新知识, 信息抽取, 语义角色, 最大熵