中文摘要：

提出了一个邻近类别集挖掘的新算法。与已有算法相比，新算法能够找到完备、正确的邻近类别集的集合，并且给出了算法正确性和完备性的理论证明。

英文摘要：

A recent work has introduced the problem of mining neighboring class sets, where instances of each class of a neighboring class set are grouped using their Euclidean distances from each other. Although the concept of neighboring class sets is a useful one, the effective computation of frequent neighboring class sets is only partially solved. A novel algorithm for mining frequent neighboring class sets from spatial datasets is presented. Compared to the previous algorithm, the algorithm can discover complete and correct frequent neighboring class sets.