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The characteristic of dynamic websites is that they include hidden contents, and this huge repository is only accessible via the website interfaces. This is a vital capability of all search engines, thus providing the users with links that are more relevant and ranked according to their needs. The drawback of most search engine algorithms is that they rank pages based on hyperlinked relative importance to other pages, rather than user intent and interest. This paper proposes a method based on Learning Automata for the classification of the webpage searches.