An Automatic Decision Support System for Assessing SDG Contributions

Monica Uttarwar; Girija Chetty

doi:10.1007/978-981-99-5085-0_1

An Automatic Decision Support System for Assessing SDG Contributions

Monica Uttarwar
, Girija Chetty

Information Systems

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

Abstract

In this paper, we propose an innovative computer-based decision support scheme based on Artificial Intelligence, consisting of novel text mining and machine learning techniques, to assess an organizational commitment to sustainable practices, with a granular analysis of the text content in their documents, and evaluate their conformance and alignment to one or more of the UN’s sustainable development goals. The proposed decision support system can help assist an organization to self-assess their business practices and marketing messages, in terms of presence in the social media channels, company documents, and refine their corporate vision and responsibility statements appropriately.

Original language	English
Title of host publication	Advances in IoT and Security with Computational Intelligence
Subtitle of host publication	Proceedings of ICAISA 2023, Volume 1
Editors	Anurag Mishra, Deepak Gupta, Girija Chetty
Place of Publication	Singapore
Publisher	Springer
Pages	1-13
Number of pages	13
Volume	1
Edition	1
ISBN (Electronic)	9789819950850
ISBN (Print)	9789819950843
DOIs	https://doi.org/10.1007/978-981-99-5085-0_1
Publication status	Published - Sept 2023
Event	International Conference on Advances in IoT, Security with AI, ICAISA 2023 - New Delhi, India Duration: 24 Mar 2023 → 25 Mar 2023

Publication series

Name	Lecture Notes in Networks and Systems
Volume	755 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	International Conference on Advances in IoT, Security with AI, ICAISA 2023
Country/Territory	India
City	New Delhi
Period	24/03/23 → 25/03/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Access to Document

10.1007/978-981-99-5085-0_1

Cite this

Uttarwar, M., & Chetty, G. (2023). An Automatic Decision Support System for Assessing SDG Contributions. In A. Mishra, D. Gupta, & G. Chetty (Eds.), Advances in IoT and Security with Computational Intelligence : Proceedings of ICAISA 2023, Volume 1 (1 ed., Vol. 1, pp. 1-13). (Lecture Notes in Networks and Systems; Vol. 755 LNNS). Springer. https://doi.org/10.1007/978-981-99-5085-0_1

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keywords = "Machine learning, SDG, Text processing",

author = "Monica Uttarwar and Girija Chetty",

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Uttarwar, M & Chetty, G 2023, An Automatic Decision Support System for Assessing SDG Contributions. in A Mishra, D Gupta & G Chetty (eds), Advances in IoT and Security with Computational Intelligence : Proceedings of ICAISA 2023, Volume 1. 1 edn, vol. 1, Lecture Notes in Networks and Systems, vol. 755 LNNS, Springer, Singapore, pp. 1-13, International Conference on Advances in IoT, Security with AI, ICAISA 2023, New Delhi, India, 24/03/23. https://doi.org/10.1007/978-981-99-5085-0_1

An Automatic Decision Support System for Assessing SDG Contributions. / Uttarwar, Monica; Chetty, Girija.
Advances in IoT and Security with Computational Intelligence : Proceedings of ICAISA 2023, Volume 1. ed. / Anurag Mishra; Deepak Gupta; Girija Chetty. Vol. 1 1. ed. Singapore: Springer, 2023. p. 1-13 (Lecture Notes in Networks and Systems; Vol. 755 LNNS).

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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PY - 2023/9

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AB - In this paper, we propose an innovative computer-based decision support scheme based on Artificial Intelligence, consisting of novel text mining and machine learning techniques, to assess an organizational commitment to sustainable practices, with a granular analysis of the text content in their documents, and evaluate their conformance and alignment to one or more of the UN’s sustainable development goals. The proposed decision support system can help assist an organization to self-assess their business practices and marketing messages, in terms of presence in the social media channels, company documents, and refine their corporate vision and responsibility statements appropriately.

KW - Machine learning

KW - SDG

KW - Text processing

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BT - Advances in IoT and Security with Computational Intelligence

A2 - Mishra, Anurag

A2 - Gupta, Deepak

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T2 - International Conference on Advances in IoT, Security with AI, ICAISA 2023

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ER -

An Automatic Decision Support System for Assessing SDG Contributions

Abstract

Publication series

Conference

UN SDGs

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