Applying dependency laws in Islamic architecture

The mining of association rules is a key area in data mining, offering insights into hidden patterns within complex datasets. While traditional (positive) association rules focus on the co-occurrence of elements, negative association rules also consider the absence of certain features, allowing for a deeper level of analysis. In this study, we propose a negative association rule-based framework aimed at identifying relationships between different architectural styles. This approach is particularly relevant in the context of Islamic architecture, where recognizing both the presence and absence of specific design elements can reveal patterns of influence, divergence, or convergence across cultures and periods. By applying our method to real-world architectural datasets, we demonstrate its effectiveness in uncovering meaningful connections that might otherwise remain hidden.

کلیدواژه ها:

Negative association rules ، data mining ، Negative itemsets