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Adaptive web has emerged as a new challenge for the semantic web. One of the aims of the adaptive web is to adapt a set of web resources to users. Over the last few years, the adaptation problem has been studied in the field of Adaptive Hypermedia. Several systems working on closed corpus resources have been developed. Currently, there is a real challenge: integrating resources available on the Web into these systems. More and more metadata describing resources are available on the Web using Semantic Web languages, and can be reused. Our objective is to build an open corpus AHS by, on the one hand, reusing AHS technologies, particularly the adaptation engine which is the heart of these systems and, on the other hand, reusing resources and their descriptions which are available on the Web. Moreover, we want to allow the creator of an adaptive system not only to reuse adaptation strategies that come with the system, but to also be able to specify his own ones. We address the problem of adaptation specification basing it on user characteristics. Existing systems either based on rules or ECA languages are complex and not easy to understand. In this paper, we propose a pattern-based approach to express adaptation strategies in a semi-automatic and simple way. This allows the creator of an adaptive system to define elementary adaptations by using and instantiating adaptation patterns. These elementary adaptations can then be combined, allowing to specify adaptation strategies in an easy and flexible manner. We distinguish adaptive navigation according to two main criteria: the selection operations performed in order to obtain resources being proposed to the user and the elements of the domain model involved in the selection process. We present a taxonomy of elementary adaptive navigation techniques. Our approach has been validated using the GLAM adaptation engine. We showed that the GLAM rules can be automatically generated from patternbased adaptations.