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Service capability, which represents the actions performed or the information delivered by a service, has become an important issue for service-oriented architecture. But most of the current semantic representation methods for service capabilities are usually based on top-down methodology and there is a gap between the semantic web services approach and the real features of web services. We aim to develop services characterization methods with statistical study on existing web services and to improve services capability representation with bottom-up software services comprehension. In this paper, the main issues for statistical study on existing web services are summarized. Two types of services characterization methods are proposed in our work: quantitative statistical study which used for probing the distribution of main objects in web services and relational statistical study which used for clustering actions or contents and measuring the similarity of web services. We conducted a statistical study on more than four hundred WSDL documents collected from XMethods.net, Amazon and Google and main quantitive statistical results are presented in this paper. A statistical relational model is proposed for mining and recognizing the patterns of services.