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Recommendation systems changed the way websites interact with users. With the huge volume of information available online, users lose much time till they find what they are looking for using the traditional statistic searching algorithms. Recommendation systems provide an intelligent solution to save users time and predict right information users are seeking for. These systems rely on collaborative similarities in contents, users' behaviors and thinking. Various techniques and approaches can be adapt to develop recommendation systems as provided through this book. This book, has been divided into six chapters. Chapter on, introduction to recommendation systems and related problems. Chapter 2, background and literature review of different recommendation approaches. Chapter 3, suggested a technique for solving cold start problem comparing to adapted various methods. Chapter 4, collaborative filtering system based the active node technique method. Chapter 5, adapting semantic information to improve the efficiency of active node approach. Chapter 6, conclusions and future research.