Tourism service providers are more and more under pressure to offer producís of greater complexity and diversity to meet the ever-changing demands of travelers; the individualistic consumption patterns and lifestyles makes it increasingly difficult for tourist service providers to anticípate consumer behavior and configure their services accordingly, i.e. the tourist industry must focus more on a "hybrid consumer" whose travel choice will be more complex. Álthough current online travel systems aim to support the customer in finding a suitable hotel or even a whole trip, most of the work is still up to the customer, who has to consider several sources of information before deciding which hotel to book. Furthermore, since the quality of a hotel room w.r.t the requirements of the end-user are multi-dimensional and cannot be easily expressed on discrete scales, the main critical issue in such cases is a price/benefit ratio which is defined by what is known, as the "best" booking. To tackle these problems an advanced search technology that considers the ratio and ranks results accordingly to the user requirements is needed. In this paper we propose a framework which uses Semantic Web technologies for an improved exploration and rating of hotels for business customers in order to reduce the search time and costs, which, in turn, results in a huge benefit for the end-users. The framework provides methods for modeling domain specific expert knowledge and integration of diverse heterogeneous data sources. Semantic technologies enable business customer to formalize their requirements and to combine those requirements with aggregated hotel information like location or features, thus achieving a selection of the hotels ranked according to the customer’s requirements.