SAO-Based Semantic Mining of Patents for Semi-Automatic Construction of a Customer Job Map
- Authors
- Lim, Joohyung; Choi, Sungchul; Lim, Chiehyeon; Kim, Kwangsoo
- Issue Date
- Aug-2017
- Publisher
- MDPI
- Keywords
- customer needs; outcome-driven innovation (ODI); job map; jobs-to-be-done; patent text mining; subject-action-object (SAO)
- Citation
- SUSTAINABILITY, v.9, no.8
- Journal Title
- SUSTAINABILITY
- Volume
- 9
- Number
- 8
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/5872
- DOI
- 10.3390/su9081386
- ISSN
- 2071-1050
- Abstract
- The Outcome-Driven Innovation (ODI) method based on the 'Jobs-to-be-done' concept is very useful in the identification of unmet customer needs and has been adopted widely in the industry. The Job Map, a tool of the ODI method, is used to understand customers by defining their behavioral process. Complications must be overcome before the Job Map can be applied to the specific problem in question, such as a time-consuming process, dealing with a large amount of data, and experts' biased work. To solve these problems, this study develops a patent mining-based method based on the subject-action-object (SAO) structure to support the creation of a Job Map by semi-automatizing data collection and analysis. This effort at better utilizing computers in customer analysis for product design will contribute to expanding computerized methods for solving design and engineering problems in practice.
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Collections - 공과대학 > 산업경영공학과 > 1. Journal Articles
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