Research on Similar Pattern Clustering in Personality Recommendation System
Tailei Wang · Jisuanji gongcheng · 2005
In the applications of recommendation systems in the E-commerce, sets, customers/clients with similar behavior need to be indentified so that people can predict customers’ interest and make quality recommendation , the key technology to produce high quality recommendation is define similarity among different objects by distances over either all or only a subset of the dimensions , some well-known distance functions are not always capture correlations among the object. The paper proposes a novel similar pattern clustering algorithm that can discover the pattern that exhibits a coherent pattern on a subset of dimensions. It shows that efficiency and wide applicability can be a suitable technique for recommender system on E-commerce site.