Nowadays, as the indices of the major search engines grow to a tremendous proportion, vertical search services can help users to find what they need. Compared with general search, obviously, shopping search's processing scope is greatly narrowed down, and thus the responding time has been decreased and the search engine's accuracy has been improved. For those reasons, shopping search engine, one of the most popular vertical search engines, makes online shopping become more and more convenient. In this paper, we propose a search results clustering approach, which is based on shopping search engine, and will help customers to browse their search results conveniently. The Shopping Search Clustering System (SSCS) is developed to organize the product lists, which are returned by a Shopping and Comparison Search. Experiment results demonstrate that its performance is close to the best known clustering engine Vivisimo.com[2], which is not only the most powerful clustering engine all of the world, but also is the exclusive launched shopping clustering engine.