Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/80194
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
Source: 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.
URI: http://scholarbank.nus.edu.sg/handle/10635/80194
Appears in Collections:Ph.D Theses (Open)

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