A New Comprehensive Patent Analysis Approach for New Product Design in Mechanical Engineering

OuYang, Kuang; Weng, Calvin S.

doi:10.1016/j.techfore.2011.02.012

Cited by 61 publications

(17 citation statements)

References 35 publications

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“…Exemplarily, Ouyang and Weng [57] develop an approach for new product design based on patent data in mechanical engineering processes. Recently, Lee, Han and Sohn [47] predict patterns of technology convergence using big data information in triadic patents.…”

Section: Technology Monitoring With Patent Datamentioning

confidence: 99%

“…We can thereby highlight dominant patterns of gamification in proprietary innovation. This study follows the ongoing trend and growing interest in applying text mining techniques in different research areas [45], especially in technical niches [5] with the use of patent data [14,15,57]. Previous patent studies in gamification relied mainly on standard information [33].…”

Section: Conclusion Limitations and Future Researchmentioning

confidence: 99%

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Gamification in Proprietary Innovation: Identifying a Technical Framework Based on Patent Data.

Hoeflinger¹

2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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Section: Technology Monitoring With Patent Datamentioning

confidence: 99%

Section: Conclusion Limitations and Future Researchmentioning

confidence: 99%

Gamification in Proprietary Innovation: Identifying a Technical Framework Based on Patent Data.

Hoeflinger¹

2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

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“…The tool, "TrendPerceptor" [12] is based on this method. TechTrees: [8] Thesaurus: [15] Level of Invention (LOI): [9] Problem Solving: [30] Innovation generation: [4] Idea generation: [30] New product development/design: [5], [6], [7], [13], [24] Technological transfer/Technology transferability: [4], [13], [14], [15], [21] Product comparison/ Similar products: [4], [17], [30] Avoid patent infringement: [20] Knowledge sharing/ extraction: [15], [16] Prior art searches: [14], [15], [16] Ontologies [e.g. Function-Behavior-Structure (FBS)] are used by Russo and Montecchi [13,14,15].…”

Section: State Of the Artmentioning

confidence: 99%

Innovation through Pertinent Patents Research based on Physical Phenomena Involved

et al. 2014

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One can find innovative solutions to complex industrial problems by looking for knowledge in patents. Traditional search using keywords in databases of patents has been widely used. Currently, different computational methods that limit human intervention have been developed. We aim to define a method to improve the search for relevant patents in order to solve industrial problems and specifically to deduce evolution opportunities. The non-automatic, semi-automatic, and automatic search methods use keywords. For a detailed keyword search, we propose as a basis the functional decomposition [1] and the analysis of the physical phenomena involved in the in the achievement of the function to fulfill. The search for solutions to design a bi-phasic separator in deep offshore shows the method presented in this paper.

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“…In addition, TF is important in MOT for research and development (R&D) planning and new product development. Consequently, there have been many studies of TF for MOT using many techniques [8,20,21]. They performed patent analysis for TF because a patent contains complete information regarding a developed technology.…”

Section: Introductionmentioning

confidence: 99%

An Interval Estimation Method of Patent Keyword Data for Sustainable Technology Forecasting

2017

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Technology forecasting (TF) is forecasting the future state of a technology. It is exciting to know the future of technologies, because technology changes the way we live and enhances the quality of our lives. In particular, TF is an important area in the management of technology (MOT) for R&D strategy and new product development. Consequently, there are many studies on TF. Patent analysis is one method of TF because patents contain substantial information regarding developed technology. The conventional methods of patent analysis are based on quantitative approaches such as statistics and machine learning. The most traditional TF methods based on patent analysis have a common problem. It is the sparsity of patent keyword data structured from collected patent documents. After preprocessing with text mining techniques, most frequencies of technological keywords in patent data have values of zero. This problem creates a disadvantage for the performance of TF, and we have trouble analyzing patent keyword data. To solve this problem, we propose an interval estimation method (IEM). Using an adjusted Wald confidence interval called the Agresti-Coull confidence interval, we construct our IEM for efficient TF. In addition, we apply the proposed method to forecast the technology of an innovative company. To show how our work can be applied in the real domain, we conduct a case study using Apple technology.

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A New Comprehensive Patent Analysis Approach for New Product Design in Mechanical Engineering

Cited by 61 publications

References 35 publications

Gamification in Proprietary Innovation: Identifying a Technical Framework Based on Patent Data.

Gamification in Proprietary Innovation: Identifying a Technical Framework Based on Patent Data.

Innovation through Pertinent Patents Research based on Physical Phenomena Involved

An Interval Estimation Method of Patent Keyword Data for Sustainable Technology Forecasting

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