Abstract
The paper proposes adaptive web recommendation system based on user behavior. The proposed system uses expert system to evaluating and recommending suitable items of content. Relevant items are subsequently evaluated and filtered based on history of visited items and user´s preferred categories of items. Main parts of the proposed system are presented and described. The proposed recommendation system is verified on specific example.
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