Model Based Smart Communication System Design

The development of natural language processing (NLP) has revealed its huge potential power and wide implementation. However, in the current status of natural language processing and smart communication design, there are some problems and limitations. First, most of the NLP and smart communication research mainly focus on the direction of the algorithm but lacks communication and relationship model design. The second, algorithm and memory implementations of models seldom separate for different tasks and situations. The third, wide use of unsupervised learning makes the model difficult to interpret, uncontrollable, and inflexible. To solve those problems, we designed memory-relationship classification categories to classify and guide the implementation of NLP and smart communication. With the implementation of model basing learning concept and communication model, we designed a sequential controllable semantic dimension and relationship dimension system to classify smart communication.