Research on the Path Sorting Efficiency of TFTA Back-Tracing Algorithm Based on the Concept of Entropy

There is often a large random arrangement in the consumer data when using TFTA back-tracing algorithm to mine and analyze the customers´ back-tracing buying behaviors in their web browse and purchase path. The disordered data structure reduces the computational efficiency and makes the result lack objectivity and practicality. The priority algorithm of path Entropy and path node entropy analysis method can identify the path with low entropy and high probability of consumption, then, advance the path of low entropy, and amend the path of high entropy. This process will help the system to change the structure of path information, improve its accuracy and degree of order, and in the end achieve the purpose of improving the efficiency of path sorting.