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

More books from Elsevier Science

Cover of the book Advances in Botanical Research by Bo Long, Yi Chang
Cover of the book Building a Travel Risk Management Program by Bo Long, Yi Chang
Cover of the book Coal and Peat Fires: A Global Perspective by Bo Long, Yi Chang
Cover of the book Major Process Equipment Maintenance and Repair by Bo Long, Yi Chang
Cover of the book Nutritional Aspects of Osteoporosis by Bo Long, Yi Chang
Cover of the book Batch and Semi-batch Reactors by Bo Long, Yi Chang
Cover of the book Solar Energy Conversion II by Bo Long, Yi Chang
Cover of the book Food Science and the Culinary Arts by Bo Long, Yi Chang
Cover of the book Information Literacy by Bo Long, Yi Chang
Cover of the book Tsunamis in the European-Mediterranean Region by Bo Long, Yi Chang
Cover of the book Soil and Environmental Chemistry by Bo Long, Yi Chang
Cover of the book Analysis of Marine Samples in Search of Bioactive Compounds by Bo Long, Yi Chang
Cover of the book Neuroendocrinology by Bo Long, Yi Chang
Cover of the book Autophagy and Cardiometabolic Diseases by Bo Long, Yi Chang
Cover of the book Differential Equations, Dynamical Systems, and an Introduction to Chaos by Bo Long, Yi Chang
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy