How to solve Ill-defined problems Intelligently in the Big Data Environment

Artificial intelligence (AI) technology has made many progresses in machine learning and closed problem solving, but the ill-defined problems are difficult to solve intelligently by AI due to the hidden insufficient knowledge and information. This paper studies the difficulties of ill-defined problem solving and analyses the directions to solve it intelligently based on Extenics in the big data environment, then knowledge intelligence expansion flowchart is presented to fill knowledge gaps of ill-defined problem solving from multi-source, heterogeneous, and massive information by human-computer interaction method to realizes the mechanism of knowledge matching. Our new research directions may improve the degree of transformation from uncertainty and randomness to inevitability in the process of solving ill-defined problems, and will promote the formation of an emerging direction of extension intelligence beyond knowledge management and artificial intelligence.