Xin Xia

Goals and objectives

Today, data miners often apply or extend AI techniques to solve problems across many domains (e.g., social media, health informatics, and software systems); while domain experts leverage their own domain knowledge to solve their own problems. Data miners often apply their automated techniques to solve a wide range of problems across different domains with limited knowledge of the domain; while domain experts often have limited knowledge of automated techniques when solving their domain-specific problems.

My research tries to bridge the gap between both types of experts (i.e., Data miners and Domain Experts). In this talk, I will focus on the software engineering domain and I will give an overview of several challenges facing data miner and domain experts as they make use of automated techniques, in particular: (1) strong performance of techniques is not sufficient, instead a deeper understanding of the domain is essential; (2) an easy approach might perform better than a complex approach; (3) results should be presented in a domain-centric context. I will present examples from my research to explain what these challenges are, why they appear, and my efforts to avoid them.