Relevance Ranking for Vertical Search Engines

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing, Internet
Cover of the book Relevance Ranking for Vertical Search Engines by Bo Long, Yi Chang, Elsevier Science
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Author: Bo Long, Yi Chang ISBN: 9780124072022
Publisher: Elsevier Science Publication: January 25, 2014
Imprint: Morgan Kaufmann Language: English
Author: Bo Long, Yi Chang
ISBN: 9780124072022
Publisher: Elsevier Science
Publication: January 25, 2014
Imprint: Morgan Kaufmann
Language: English

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
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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