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Constructing Patent Maps Using Text Mining to Sustainably Detect Potential Technological Opportunities

机译:使用文本挖掘构建专利地图,可持续地检测潜在的技术机会

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摘要

With the advent of the knowledge economy, firms often compete for intellectual property rights. Being the first to acquire high-potential patents can assist firms in achieving future competitive advantages. To identify patents capable of being developed, firms often search for a focus by using existing patent documents. Because of the rapid development of technology, the number of patent documents is immense. A prominent topic among current firms is how to use this large number of patent documents to discover new business opportunities while avoiding conflicts with existing patents. In the search for technological opportunities, a crucial task is to present results in the form of an easily understood visualization. Currently, natural language processing can help in achieving this goal. In natural language processing, word sense disambiguation (WSD) is the problem of determining which “sense” (meaning) of a word is activated in a given context. Given a word and its possible senses, as defined by a dictionary, we classify the occurrence of a word in context into one or more of its sense classes. The features of the context (such as neighboring words) provide evidence for these classifications. The current method for patent document analysis warrants improvement in areas, such as the analysis of many dimensions and the development of recommendation methods. This study proposes a visualization method that supports semantics, reduces the number of dimensions formed by terms, and can easily be understood by users. Since polysemous words occur frequently in patent documents, we also propose a WSD method to decrease the calculated degrees of distortion between terms. An analysis of outlier distributions is used to construct a patent map capable of distinguishing similar patents. During the development of new strategies, the constructed patent map can assist firms in understanding patent distributions in commercial areas, thereby preventing patent infringement caused by the development of similar technologies. Subsequently, technological opportunities can be recommended according to the patent map, aiding firms in assessing relevant patents in commercial areas early and sustainably achieving future competitive advantages.
机译:随着知识经济的出现,公司经常争夺知识产权。成为第一个获取高潜在专利的人可以帮助公司实现未来的竞争优势。为了确定能够开发的专利,公司通常通过使用现有专利文献来搜索重点。由于技术的快速发展,专利文件的数量是巨大的。当前公司之间的突出主题是如何使用这笔大量专利文档来发现新的商机,同时避免与现有专利的冲突。在寻找技术机会的过程中,至关重要的任务是以易于理解的形式呈现结果。目前,自然语言处理可以帮助实现这一目标。在自然语言处理中,词感歧义(WSD)是确定在给定上下文中激活单词的“感觉”(含义)的问题。鉴于由字典定义的单词及其可能的感官,我们将上下文中的一个单词的发生分类为一个或多个Sense类。上下文的特征(例如邻近单词)为这些分类提供了证据。专利文献分析的目前方法认证区域的改进,例如对许多维度的分析和推荐方法的发展。本研究提出了一种支持语义的可视化方法,减少了术语所形成的尺寸的数量,并且可以通过用户容易地理解。由于在专利文献中经常发生多园词,我们还提出了一种WSD方法来减少术语之间计算的失真程度。对异常值分布的分析用于构建能够区分类似专利的专利映射。在开发新战略期间,建设专利地图可以帮助公司了解商业领域的专利分布,从而防止由类似技术的发展引起的专利侵权。随后,可以根据专利地图推荐技术机会,援助公司在早期和可持续地实现未来的竞争优势中评估商业领域的相关专利。

著录项

  • 作者

    Hei Wang; Yung Chi; Ping Hsin;

  • 作者单位
  • 年度 2018
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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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