In plain, uncomplicated language, and using detailed examples to explain the key concepts, models, and algorithms in vertical search ranking, _Relevance Ranking for Vertical Search Engines_ teaches readers how to manipulate ranking algorithms to achieve better results in real-world applications. This reference book for professionals covers concepts and theories from the fundamental to the advanced, such as relevance, query intention, location-based relevance ranking, and cross-property ranking. It covers the most recent developments in vertical search ranking applications, such as freshness-based relevance theory for new search applications, location-based relevance theory for local search applications, and cross-property ranking theory for applications involving multiple verticals. * Foreword by Ron Brachman, Chief Scientist and Head, Yahoo! Labs * Introduces ranking algorithms and teaches readers how to manipulate ranking algorithms for the best results * Covers concepts and theories from the fundamental to the advanced * Discusses the state of the art: development of theories and practices in vertical search ranking applications * Includes detailed examples, case studies and real-world situations