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

Junfang Guo, Xuefeng Wang*, Qianrui Li, Donghua Zhu

*此作品的通讯作者

    科研成果: 期刊稿件文章同行评审

    70 引用 (Scopus)

    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.

    源语言英语
    页(从-至)27-40
    页数14
    期刊Technological Forecasting and Social Change
    105
    DOI
    出版状态已出版 - 1 4月 2016

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    Guo, J., Wang, X., Li, Q., & Zhu, D. (2016). Subject-action-object-based morphology analysis for determining the direction of technological change. Technological Forecasting and Social Change, 105, 27-40. https://doi.org/10.1016/j.techfore.2016.01.028