Analysis of Supervised Text Classification Algorithms on Corporate Sustainability Reports

摘要：

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.

关键词： Machine Learning Feature Selection Text Classification Document Categorization Supervised Learning Corporate Sustainability Report GRI

作者: Amir Mohammad Shahi Biju Issac Jashua Rajesh Modapothala

作者单位: School of Engineering, Computing and Science School of Business and Design Swinburne University of Technology (Sarawak Campus)Kuching, Malaysia

会议类型: 国际会议

会议名称: 2011 International Conference on Computer Science and Network Technology(2011计算机科学与网络技术国际会议 ICCSNT 2011)

会议地点: 哈尔滨

会议语种:英文

页码: 96-100

在线出版日期: 2011-12-24（万方平台首次上网日期，不代表论文的发表时间）