Abstract

In recent years, as the importance of user innovation has become more important, enterprises have started to demand efficient and systematic user needs analysis for their products or services. Although opinion mining research based on a large number of online reviews available has been actively conducted recently, most existing studies that analyze user needs for technology development have provided inaccurate results due to the differences in vocabulary that exist between databases holding social data and patents. Motivated by this problem, we propose an approach to exploring technology opportunities that analyzes the subject-action-object (SAO) structures found in both patents and user reviews. To achieve this, we first carried out a sentiment analysis on user-review sentences linked to user needs, from this SAO analysis we extracted ample information related to technological structures contained in the reviews. Second, since in patent analysis, patent documents are structured in terms of the technological elements present, we extracted the technology’s SAO structures using their F-term code that contains multidimensional information available in this technology classification system. Finally, we vectorized the SAO structures derived from the reviews and patent documents using SAO2Vec before calculating the cosine similarity between SAOs in order to connect the reviews and patents. By applying the method proposed in this study to the automobile field, we present technological opportunities found in patents to address user needs found in automobile reviews.

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