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Deriving technology intelligence from patents: Preposition-based semantic analysis
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DOI：10.1016/j.joi.2018.01.001.png)
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摘要
En 中文
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.
Keyword:
Technology intelligence
Technology search
Technology trends
Patent analysis
Semantic
Preposition
Text mining
Key-words
Text mining
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.5
论文数:
1.6K
被引数:
7.9K
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