SAS, the leader in business analytics and services, and the Department of Statistics and Actuarial Science of the University of Hong Kong today announced the winning teams of the Innovative Data Mining Application Awards. This is the tenth consecutive year the world’s largest privately owned software company has sponsored the local University with the data mining awards, and provided data mining software to the department for nurturing high caliber professionals in the analytics landscape.
The Innovative Data Mining Application Awards 2015 invited students from the Master’s program of the Department of Statistics and Actuarial Science to submit proposals using scientific analytic tools to analyze data collected in different aspects, such as sports, food & beverage, social media and marketing skills, to address real-life issues.
The project “Star Miners”, developed by JIN Zhe, PAN Yuxing and SHE Shichang, was selected as the champion of the competition. Their creativity in applying data mining to NBA talent selection was highly regarded by the judges. The first runner-up goes to the project done by Cheung Chi Hin, Cheung Sek Yuen Martin, Kwan Ming Tsun and Lam Wing Yin, which aims to leverage on data mining to help customers with wine selection. The second runner-up goes to two teams, one of them made up of Cheung Kai Chun, Huang Jia Jie and Yip Ka Man, which studied food photo shooting patterns and posting habits of Hong Kong Instagram users, and the other formed by Cheung Wing Chung Vinci, Lau Kwok Piu and Lo Sze Nok Johnathan, which developed a predictive model to support effective bank telemarketing. All of these winning projects serve to prove the power of analytics and provide new insights to appreciate daily life phenomena from a data analytics perspective.
Officiating at the award ceremony, Wilson Ho, General Manager, SAS Hong Kong, said, “It is once again our great pleasure to sponsor these awards and provide SAS software to the Department of Statistics and Actuarial Science at the University of Hong Kong, to support this meaningful award and provide an opportunity for talented students to unleash their creativity in undertaking data mining projects with the use of our advanced software. I am impressed by all of the winning projects this year in terms of their creativity and positive impacts on our everyday lives.”
Dr. Philip Yu, Associate Professor of the University of Hong Kong’s Department of Statistics and Actuarial Science, also recognized the achievement of the students and SAS’s contribution at the ceremony: “It is delightful to see students making good and ingenious use of the data available in daily life, and turning them into innovative and valuable insights. They have truly demonstrated outstanding ideas in the application of data analytics in our daily life. I am also pleased to share a similar vision of education with SAS. The department highly appreciates SAS Hong Kong for their generous support of these course projects over the years.”
SAS remains committed to supporting educational institutes so that students can have the greatest opportunity to develop their potential, especially in advancing their career aspirations in analytics and data science. As part of an established initiative to support students with mathematical and statistical abilities in developing their careers and preparing them to meet industry demands, it is one of the core focuses of SAS Corporate Social Responsibilities in committing efforts and resources to the education sector.
The Department of Statistics and Actuarial Science of the University of Hong Kong has been offering the Data Mining Techniques course for the Master of Statistics Program since 2003. Students are taught with real-life examples enabling them to apply their acquired knowledge in the workplace. Toward the end of each academic year, students are assigned a group project, allowing them to demonstrate data mining skills with the use of SAS tools. The Innovative Data Mining Application Award has recognized talented students' projects in the SAS® Enterprise Miner course since 2006.