A Novel Method Considering Guesses and Slips for Item Ordering: Noise-Filter Ordering Theory and Item Relational Structure Theory

art's ordering theory algorithm and Takeya's item relational structure algorithm are the two classical ordering algorithms, but both of them have a common problem, that is, the item ordering results depend on the setting of threshold. The reason for this problem is that the ordering index fluctuates greatly due to guessing and slipping noise. This paper presents an improved algorithm, which can effectively filter out the noise of guessing and slipping. It is more effective than the two traditional methods. This paper also develops a computer program and carries out simulation experiments to prove the advantages of this method.