https://edu.cnblogs.com/campus/gdwywm/se1803/homework/3471
1. This semester encoding will follow the coding conventions of the following links:
https://www.jianshu.com/p/d7e87107073c
2. Read the contents of the "mathematical beauty" in the chapter 'Applying the Theory of Information Processing', etc., to understand the concept of entropy in information theory and 'mutual information', 'relative entropy', etc. for the measure. Entropy is the uncertainty of the beam can be used to measure the quality of statistical language models; 'interoperability information' is a measure of correlation between two random events, encountered in natural language processing, machine translation meaning ambiguous when the effective application problem; relative entropy is a measure of two positive functions are similar, for the same function, relative entropy is equal to zero, the utility of the information retrieval and comparison. Because the amount of information to be processed is very large, the algorithm has obvious necessity to optimize the process to achieve them.
3. The term hope to use a software algorithm information than for function.