Intelligent Corporate Sustainability report scoring solution using machine learning approach to text categorization

Shahi, Amir Mohammad, Issac, Biju and Modapothala, Jashua Rajesh (2013) Intelligent Corporate Sustainability report scoring solution using machine learning approach to text categorization. In: STUDENT 2012 - 3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, 6th - 9th October 2012, Kuala Lumpur, Malaysia.

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/STUDENT.2012.6408409

Abstract

Development of an intelligent software system to analyze and score Corporate Sustainability reports within the Global Reporting Initiative (GRI) framework has been well foreseen and in a high demand since the latest framework's publication in 2000's. As the number of reporting organizations and published reports is increasing exponentially, development of a software system to automate the daunting manual scoring process seems even more vital. We describe our preliminary efforts and the related results of our efforts in building such software through application of machine learning approach to text classification. Conduction of earlier training on thousands of sample documents to construct machine learning based classifiers inductively is our primary approach to solving this problem.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Global reporting initiative, GRI, CSR, corporate sustainability report, machine learning, feature selection, NaiveBayes
Subjects: G400 Computer Science
G700 Artificial Intelligence
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 18 Dec 2018 10:28
Last Modified: 18 Dec 2018 10:28
URI: http://nrl.northumbria.ac.uk/id/eprint/37321

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