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Deriving technology intelligence from patents: Preposition-based semantic analysis

机译:从专利中获取技术智能:基于介词的语义分析

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摘要

Patents are one of the most reliable sources of technology intelligence, and the true value of patent analysis stems from its capability of describing the content of technology based on the relationships between keywords. To date a number of techniques for analyzing the information contained in patent documents that focus on the relationships between keywords have been suggested. However, a drawback of the existing keyword approaches is that they cannot yet determine the types of relationships between the keywords. This study proposes a novel approach based on preposition semantic analysis network which overcomes the limitations of the existing keywords-based network analysis and demonstrates its potential through an application. A preposition is a word that defines the relationship between two neighboring words, and, in the case of patents, prepositions aid in revealing the relationships between keywords related to technologies. To demonstrate the approach, patents regarding an electric vehicle were employed. 13 prepositions were identified which could be used to define 5 relationships between neighboring technological terms: "inclusion (utilization)," "objective (purpose)," "effect," "process," and "likeness." The proposed approach is expected to improve the usability of keyword-based patent analyses and support more elaborate studies on patent documents. (C) 2018 Elsevier Ltd. All rights reserved.
机译:专利是最可靠的技术情报来源之一,专利分析的真正价值在于其基于关键字之间的关系描述技术内容的能力。迄今为止,已经提出了许多分析专利文件中包含的信息的技术,这些技术着重于关键词之间的关系。但是,现有关键字方法的缺点是它们还不能确定关键字之间的关系类型。这项研究提出了一种基于介词语义分析网络的新方法,该方法克服了现有基于关键字的网络分析的局限性,并通过应用程序展示了其潜力。介词是定义两个相邻词之间关系的词,对于专利而言,介词有助于揭示与技术相关的关键字之间的关系。为了演示该方法,采用了有关电动汽车的专利。确定了13个介词,它们可用于定义相邻技术术语之间的5种关系:“包含(利用),“客观(目的)”,“效果”,“过程”和“相似性”。预期所提出的方法将改善基于关键字的专利分析的可用性,并支持对专利文件进行更详尽的研究。 (C)2018 Elsevier Ltd.保留所有权利。

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