Please use this identifier to cite or link to this item:
Title: Studies on Machine Learning for Data Analytics in Business Application
Authors: FANG FANG
Keywords: Data Analytics; Machine Learning; Data Mining; Sentiment Classification; Topic Modeling; Industry Classification
Issue Date: 22-Jan-2014
Citation: FANG FANG (2014-01-22). Studies on Machine Learning for Data Analytics in Business Application. ScholarBank@NUS Repository.
Abstract: The volume of data produced by the digital world is now growing at an unprecedented rate. Data are being produced everywhere, from Facebook, Twitter, YouTube to Google search records, and more recently, mobile apps. The tremendous amount of data embodies incredible valuable information. Analysis of data, both structured and unstructured such as text, is important and useful to a number of groups of people such as marketers, retailers, investors, and consumers. In this thesis, we focus on predictive analytics problems in the context of business applications and utilize machine learning methods to solve them. Specifically, we focus on 3 problems that can support a firm?s business and management team?s decision-making. We follow the Design Science Research Methodology to conduct the studies.
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Thesis_R_Final.pdf1.31 MBAdobe PDF



Page view(s)

checked on Apr 20, 2019


checked on Apr 20, 2019

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.