The article introduces an algorithm for reducing attributes in decision tables, aiming to simplify rule sets. By using information entropy, the algorithm seeks to find the smallest set of attributes needed. The researchers also propose a method to efficiently find similar objects based on sorting and binary search, improving the algorithm's effectiveness.