Abstract
This paper presents a semi-automated state of the art related to the concept of circular economy and focuses on technical problems identification methods based on syntactic dependency patterns, for ameliorating supervised state of the art and patent intelligence. The data and information used in this paper were collected from patents and scientific publications dataset. Through parsing the patent text, very precise lists of recycling materials are automatically extracted without the user being an expert in the problems of the sector. An exemplary case dealing with circular economy is proposed, stressing what types of business areas are nowadays related the most from the materials that are being recycled. This paper contains the results of this analysis and the related comments.
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Spreafico, M., Fayemi, PE., Bersano, G. (2019). An Investigation of the Relations on Business Areas and Recycled Materials in Circular Economy. In: Ball, P., Huaccho Huatuco, L., Howlett, R., Setchi, R. (eds) Sustainable Design and Manufacturing 2019. KES-SDM 2019. Smart Innovation, Systems and Technologies, vol 155. Springer, Singapore. https://doi.org/10.1007/978-981-13-9271-9_18
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DOI: https://doi.org/10.1007/978-981-13-9271-9_18
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