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

Amir Mohammad Shahi*, Biju Issac, Jashua Rajesh Modapothala

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012 - Conference Booklet
PublisherIEEE
Pages227-232
Number of pages6
ISBN (Electronic)9781467317054
ISBN (Print)9781467316491
DOIs
Publication statusPublished - 11 Jan 2013
Event3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012 - Kuala Lumpur, Malaysia
Duration: 6 Oct 20129 Oct 2012

Conference

Conference3rd IEEE Conference on Sustainable Utilization and Development in Engineering and Technology, STUDENT 2012
CountryMalaysia
CityKuala Lumpur
Period6/10/129/10/12

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