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A collaboration platform for enabling industrial symbiosis : towards creating a self-learning waste-to-resource database for recommending industrial symbiosis transactions using text analytics

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Yeo, Zhiquan, Choong Low, Jonathan Sze, Loong Tan, Daren Zong, Chung, Si Ying, Tjandra, Tobias Bestari and Ignatius, Joshua (2019) A collaboration platform for enabling industrial symbiosis : towards creating a self-learning waste-to-resource database for recommending industrial symbiosis transactions using text analytics. In: 26th CIRP Conference on Life Cycle Engineering, Purdue University, West Lafayette, IN, May 7-9 2019. Published in: Procedia CIRP, 80 pp. 643-648. ISSN 2212-8271. doi:10.1016/j.procir.2019.01.015

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Official URL: https://doi.org/10.1016/j.procir.2019.01.015

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Abstract

Industrial Symbiosis (IS) adopts a collaborative approach, which aims to re-channel resources – traditionally considered spent and non-productive – towards alternative value-adding pathways. Empirically, the concept of IS has been rapidly implemented in practice through a facilitated approach, whereby businesses are engaged and “match-made” via a facilitating body. While recommending alternative pathways for companies to establish IS-based transactions is a long-standing practice, recent technological advancement has shifted the nature of this task from one that is based purely on human intellect and reasoning, towards one which leverages intelligent recommendation algorithms to provide relevant suggestions. Traditionally, these recommendation engines rely on manually populated knowledge bases that are not only labor-intensive to build but also costly to maintain. This work presents the creation of a self-learning waste-to-resource database supporting an IS recommendation system by utilizing text analytics techniques. We further demonstrate its practical application to support IS facilitating bodies in their core activity.

Item Type: Conference Item (Paper)
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TS Manufactures
Divisions: Faculty of Science > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH): Industrial ecology , Materials management -- Databases, Machine learning, Industrial ecology -- Databases
Journal or Publication Title: Procedia CIRP
Publisher: Elsevier
ISSN: 2212-8271
Official Date: 2019
Dates:
DateEvent
2019Published
4 May 2019Available
1 February 2019Accepted
Date of first compliant deposit: 30 July 2020
Volume: 80
Page Range: pp. 643-648
DOI: 10.1016/j.procir.2019.01.015
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
Conference Paper Type: Paper
Title of Event: 26th CIRP Conference on Life Cycle Engineering
Type of Event: Conference
Location of Event: Purdue University, West Lafayette, IN
Date(s) of Event: May 7-9 2019

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