Tracking and memorizing mechanism in machine translation

Improving the machine intelligence and the quality of machine translation is always an important and hard problem in natural language processing. This paper analyzes the disadvantages of present translation systems, and proposes a track-memorizing mechanism that is based on machine learning. Then, the principles of the mechanism are elaborated. At the end, we describe and discuss the utilization of the approach in Russian-Chinese translation system.