- Print ISBN 9780124071711
- Electronic ISBN 9780124072022
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.
Software Engineers, Computer Scientists, Academic Researchers, Applied Scientists Web professionals and Researchers.
"The authors of this book are active researchers in vertical search technology. This book provides researchers and application developers a comprehensive overview of the general concepts, techniques, and applications in vertical search."
-Prabhakar Raghavan, Vice President of Engineering at Google
"This is an excellent book that gives the first and comprehensive introduction and overview on vertical search, an emerging and important field!
Researchers and practitioners will find this book provides a comprehensive overview and systematic treatment on theories, methodologies and practices for vertical search ranking, covering several very promising topics, such as search on news and medical information, entity search, mobile search, as well as multi-aspect ranking, aggregating vertical search ranking and cross vertical ranking.
I found it a great pleasure to read!"
-Jiawei Han, Abel Bliss Professor, Department of Computer Science, Univ. of Illinois at Urbana-Champaign