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NPMI (left) and word vector cosine similarity (right) matrices for waste flows (transactions) and waste receivers (acceptors) in the TEDA EIP. Red squares indicate verified exchanges from the EIP case studies. The color scale is from white (0 or no data) to black (1). Information regarding underlying data for this figure is available in Section S.2 of the Supporting Information

NPMI (left) and word vector cosine similarity (right) matrices for waste flows (transactions) and waste receivers (acceptors) in the TEDA EIP. Red squares indicate verified exchanges from the EIP case studies. The color scale is from white (0 or no data) to black (1). Information regarding underlying data for this figure is available in Section S.2 of the Supporting Information

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A challenge of facilitating industrial symbiosis involves identifying novel uses of waste streams that can satisfy the demands of other industries. For these efforts, a variety of characteristics must often be considered. A mine of relevant knowledge has been gathered in resources such as academic journals and patent databases. However, in looking...

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Citations

... A much more open-ended type of data extraction, based on Natural Language Processing (NLP), is showcased by Davis and Aid (2021). This study demonstrates the applicability of extracting from the literature "word vectors" associated with waste stream properties and with industrial input properties, so as to identify word-vector correlations and suggest potential industrial symbiosis opportunities. ...
... Characterizing material stocks, especially infrastructures, is also increasingly facilitated by novel data acquisition and analysis techniques (Arbabi et al., 2021;Ebrahimi et al., 2021;Sprecher et al., 2021;Vilaysouk et al., 2021;Zhou et al., 2021). In particular, waste management and recirculation strategies are propelling a very diverse set of novel data-driven research (Ballatore et al., 2021;Davis & Aid, 2021;Kerdlap et al., 2021;Zhou et al., 2021). ...
... Expanding the dataset with more industrial sectors and a wider variety of streams and exchanges can be considered a next step towards an enhanced map of potential hubs. Further research could focus on integrating a machine-learning algorithm to include affinity parameters beyond distance and the number of surrounding points (Davis & Aid, 2022). Although obtaining the required data is recognised as the basic challenge, the digital revolution across industries looks promising to identify further opportunities for developing circularity solutions (Barile et al., 2021). ...
... In the present study the categories were defined by inspection according to references in the literature; for more sophisticated techniques, a higher amount of data is required (Davis & Aid, 2022). IS case-base: Industrial Symbiosis profiles in energy-intensive industries ...
... Strategies for IS matchmaking have advantages and disadvantages depending on the sophistication level (Davis & Aid, 2022). A first IS strategy is to match streams by names. ...
Thesis
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