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Wireless Sensor Networks are attracting lots of attention for its broad application areas, and hence the services provided by WSNs become much more diverse. But with the development of in-depth applications, service discovery and composition are challenges to the end users. Service mining is a new technique in Internet which can discover new composite services from the abundantly existing services in Internet to meet the users' needs. However, those service mining methods are not practical in the energy-exhausted and application-oriented WSNs. In this paper, we develop a semantics-based service mining method for WSNs, to provide users with interesting composite services. In this method, services are combined and recommended to users actively according to the calculation of service similarity and an up datable semantic database. By the results of service similarity, useless compositions are filtered out so that energy consumption on service flooding can be reduced. The update strategy of semantic database is also given out, by which the composite services can keep up with time and be more applicative. The benefits of the proposed method are that all operations such as calculating, filtering, and updating are simple enough and can be performed at broker nodes.