<p>In plain, uncomplicated language, and using detailed examples to explain the key concepts, models, and algorithms in vertical search ranking, <i>Relevance Ranking for Vertical Search Engines</i> teaches readers how to manipulate ranking algorithms to achieve better results in real-world applications. </p> <p>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. </p><ul><li>Introduces ranking algorithms and teaches readers how to manipulate ranking algorithms for the best results</li><li>Covers concepts and theories from the fundamental to the advanced</li><li>Discusses the state of the art: development of theories and practices in vertical search ranking applications</li><li>Includes detailed examples, case studies and real-world examples</li></ul>