Relevance Ranking for Vertical Search Engines

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.

  • 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 examples

Table of Contents
Chapter 1. Introduction
Chapter 2. News Search Ranking
Chapter 3. Medical Domain Search Ranking
Chapter 4. visual Search Ranking
Chapter 5. Mobile Search Ranking
Chapter 6. Multi-Aspect Relevance Ranking
Chapter 7. Entity Ranking
Chapter 8. Aggregrated Vertical Search
Chapter 9. Cross Vertical Search Ranking

Book Details

  • Paperback: 264 pages
  • Publisher: Morgan Kaufmann (February 2014)
  • Language: English
  • ISBN-10: 0124071716
  • ISBN-13: 978-0124071711
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