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Subject-action-object-based morphology analysis for determining the direction of technological change

机译:基于主体-行为-对象的形态学分析,以确定技术变革的方向

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摘要

Morphology analysis, despite being a strong stimulus for the development of new alternatives, largely relies on domain experts and neglects the relationships between keywords in the construction of morphological structures. In addition, there are few systematic approaches to prioritize the morphological configurations. To address these issues, a hybrid approach is proposed, which enhances the performance of morphology analysis by combining it with subject-action-object (SAO) semantic analysis. Initially, a keyword co-occurrence patent set for subsequent SAO analysis is prepared based on keywords frequency vector analysis. Then, SAO structures are extracted and semantic analysis is performed to identify the relationships between keywords, which help to build morphological structures more objectively. In addition, a well-defined evaluation system that contains eight sub-indexes is proposed to evaluate the morphological configurations. Finally, to demonstrate and validate the proposed approach, the dye-sensitized solar cells technology is employed as the case study. Results indicate that the most promising combination we predict appears frequently in 2012-2014 and the distribution of it is also close to the fact in 2012-2014. Accordingly, the proposed method can be used to effectively determine the direction of technological change and to forecast technology innovation opportunities. (C) 2016 Elsevier Inc. All rights reserved.
机译:形态分析尽管是开发新替代方法的强大动力,但在很大程度上依赖于领域专家,并且在构建形态结构时忽略了关键字之间的关系。另外,很少有系统的方法可以对形态构型进行优先排序。为了解决这些问题,提出了一种混合方法,该方法通过将形态分析与主语-主体-对象(SAO)语义分析相结合来增强形态分析的性能。最初,基于关键词频率矢量分析,准备用于后续SAO分析的关键词共现专利集。然后,提取SAO结构并进行语义分析以识别关键字之间的关系,这有助于更客观地构建形态结构。另外,提出了一个定义明确的评估系统,该系统包含八个子索引来评估形态构型。最后,为了证明和验证所提出的方法,以染料敏化太阳能电池技术为案例研究。结果表明,我们预测的最有希望的组合会在2012-2014年频繁出现,而且其分布也接近于2012-2014年的事实。因此,所提出的方法可用于有效地确定技术变革的方向并预测技术创新机会。 (C)2016 Elsevier Inc.保留所有权利。

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