دورية أكاديمية
Toward building recommender systems for the circular economy: Exploring the perils of the European Waste Catalogue.
| العنوان: | Toward building recommender systems for the circular economy: Exploring the perils of the European Waste Catalogue. |
|---|---|
| المؤلفون: | van Capelleveen G; Department of Industrial Engineering and Business Information Systems, University of Twente, the Netherlands. Electronic address: g.c.vancapelleveen@utwente.nl., Amrit C; Faculty of Economics and Business Section Operations Management, University of Amsterdam, the Netherlands., Zijm H; Department of Industrial Engineering and Business Information Systems, University of Twente, the Netherlands., Yazan DM; Department of Industrial Engineering and Business Information Systems, University of Twente, the Netherlands., Abdi A; Department of Industrial Engineering and Business Information Systems, University of Twente, the Netherlands. |
| المصدر: | Journal of environmental management [J Environ Manage] 2021 Jan 01; Vol. 277, pp. 111430. Date of Electronic Publication: 2020 Oct 16. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Academic Press Country of Publication: England NLM ID: 0401664 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1095-8630 (Electronic) Linking ISSN: 03014797 NLM ISO Abbreviation: J Environ Manage Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: London ; New York, Academic Press. |
| مواضيع طبية MeSH: | Algorithms* , Semantics*, Commerce ; Comprehension |
| مستخلص: | The growth in the number of industries aiming at more sustainable business processes is driving the use of the European Waste Catalogue (EWC). For example, the identification of industrial symbiosis opportunities, in which a user-generated item description has to be annotated with exactly one EWC tag from an a priori defined tag ontology. This study aims to help researchers understand the perils of the EWC when building a recommender system based on natural language processing techniques. We experiment with semantic enhancement (an EWC thesaurus) and the linguistic contexts of words (learned by Word2vec) for detecting term vector similarity in addition to direct term matching algorithms, which often fail to detect an identical term in the short text generated by users. Our in-depth analysis provides an insight into why the different recommenders were unable to generate a correct annotation and motivates a discussion on the current design of the EWC system. (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Circular economy; European waste catalogue (EWC); Industrial symbiosis; Recommender system; Tag recommendation |
| تواريخ الأحداث: | Date Created: 20201019 Date Completed: 20201125 Latest Revision: 20201125 |
| رمز التحديث: | 20231215 |
| DOI: | 10.1016/j.jenvman.2020.111430 |
| PMID: | 33075657 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1095-8630 |
|---|---|
| DOI: | 10.1016/j.jenvman.2020.111430 |