Nihon Kikai Gakkai ronbunshu (Jan 2022)
Design concept generation from patent information based on novelty potential and distributional word representation model
Abstract
Generating novel design concepts in the conceptual design phase is a cornerstone for producing innovative products. This paper proposes a method to support the generation of new design concepts from patent documents. The proposed method is based on the theory of novelty potential that the combination of abstract concepts leads to the generation of the novel design concept and that the distance between the combined abstract concepts correlates to the possibility of generating it. This research adopts the distributed word representation model of word2vec to extract abstract concepts from patent documents and to measure the concept distance. The two matrices are introduced to visualize the relationships of the extracted abstract concepts; the novelty potential matrix which shows the value of the novelty potential between the abstract concepts, and the void matrix which shows the numbers of existing patents of the abstract concepts. They help a designer to identify the combinations of abstract concepts that are high novelty potential and no existing patent. This paper demonstrates a case study of generating novel ideas of sports business with blockchain using the proposed method. The results show its uniqueness and effectiveness.
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