DocumentCode
1729914
Title
Analysis of supervised text classification algorithms on corporate sustainability reports
Author
Shahi, Amir Mohammad ; Issac, Biju ; Modapothala, Jashua Rajesh
Author_Institution
Sch. of Eng., Comput. & Sci., Swinburne Univ. of Technol., Kuching, Malaysia
Volume
1
fYear
2011
Firstpage
96
Lastpage
100
Abstract
Machine Learning approach to text classification has been the dominant method in the research and application field since it was first introduced in the 1990s. It has been proven that document classification applications based on Machine Learning produce competitive results to those based on the Knowledge Based approaches. This approach has been widely researched upon as well as applied in various applications to solve various text categorization problems. In this research we have applied such techniques in a novel effort to find out which document classification algorithms perform best on Corporate Sustainability Reports.
Keywords
learning (artificial intelligence); pattern classification; report generators; text analysis; corporate sustainability reports; document classification algorithm; knowledge based approach; machine learning; supervised text classification algorithm; text categorization problem; Artificial neural networks; Niobium; Corporate Sustainability Report; Document Categorization; Feature Selection; GRI; Machine Learning; Supervised Learning; Text Classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4577-1586-0
Type
conf
DOI
10.1109/ICCSNT.2011.6181917
Filename
6181917
Link To Document