Applying meta search systems is a suitable method to support the user if there are many different services. Due to information splitting strategies of literature services existing meta systems either provide minimal integration or slow response times. The proposed approach combines techniques of personalization and query optimization in order to satisfy the user’s demand for fast and comprehensive results. This approach deploys a new personalization technique, called generic search strategies. The designed query language for meta search systems contains soft conditions and a top k operator in order to create the potential for query optimization. For validation, this approach employs experiments to evaluate and compare different query processing strategies. Finally, these experiments will permit to identify the contribution of certain parts of user profiles to query optimization.