Imagination: application of the Harman tree

I recently learned the Harman tree (the optimal binary tree) in the data structure. It means that the given number of leaves has different weights, minimum the weighted paths from the root to the leaves.

I have learned some basic applications, such as data encoding: Assume that 26 letters and 9 numbers appear in a document, only 6-10 characters in a letter have a high probability (the weight is relatively large). How can we minimize the total length of these characters by giving them different paths. Achieve better compressionAlgorithm.

In terms of social decision-making and judgment, for example, the NPC and CPPCC: deputies to the National People's Congress have relatively large weights. Therefore, they are given a relatively close "path" from the central government and can directly provide suggestions; ordinary people have small weights. Of course, the "path" is far away.) If you want to have an appeal or suggestion, you have to follow the "path" of towns, counties, cities, and provinces. Of course, the management layer believes that the purpose of putting ordinary people with relatively small weights on the treasure of a binary tree (far away from the root node) is to achieve the overall path and minimum, in real world, where is it reflected? Let me give you a thought... I haven't figured it out... (reducing the cost? Is it more efficient to obtain information ?)

Your place ......

Any comments are welcome.