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Featured Research

      The Management Studies Research Center is devoted to the research on management by increasing the opportunities on teamwork researching and promoting cross-discipline and international collaborative research. The following shows some of our ongoing efforts:


1.Applying Big Data Analytics to Promote Labor Income

       To cope with the vast volume, variety and veracity of big data, we plan to build our analytics tools on top of cluster computing platform. As illustrated in Figure 1, this platform can seamlessly support four types of big data analytic tasks – Data E.T.L. (Extract, Transform & Load), Visualization, Prototyping and Full-Scale Modeling.

Step 1. ETL – Extract, Transform & Load
Big data analytics depends heavily on parallel computations. Before analysis, massive datasets need to be extracted from its original storages, transformed into proper formats and loaded into distributed file system.
Step 2. Visualization
Data Visualization helps to identify issues before and present results after detail analysis.
Step 3. Prototyping
we choose to conduct two-stage modeling. Before building full-scale models, we’d extract samples (up to around 4 gigabytes, bounded by the limit of main memory in most working data nodes) and build prototype models for concept proving.
Step 4. Full-Scale Models
In addition to Spark’s libraries, we would also incorporate its built-in languages – Python, Scala, and Spark machine learning libraries (MLlibs).
2.ASE Social Listening For Global
       This project aims to analyze articles collected from online news, social media, and discussion forums. These articles could be expressed in multiple languages as they are from different countries. The research topics involved in this project include identifying topics and sentiments inherent in these articles. The research results will help the international enterprise in tracking global market responses.
3.The Framework Development of Taiwan Feature Identification
       This project aims to develop a framework that identifies unique features pertaining to Taiwan. These features could be essential in distinguishing Taiwan and attracting foreign tourists. Service science methodologies are employed to develop the framework and subsequently design tours, especially in Kaohsiung area.