Research on decision tree induction from self-map space based on web

This paper proposes an improved decision tree method for web information retrieval with self-map attributes. Our self-map tree has a value of self-map attribute in its internal node, and information based on dissimilarity between a pair of map sequences. Our method selects self-map which exists between data by exhaustive search based on relation and attribute information. Experimental results confirm that our improved method constructs comprehensive and accurate decision tree. Moreover, an example shows that our self-map decision tree is promising for data mining and knowledge discovery.