Relevance Ranking for Vertical Search Engines
Published on 14. May 2014
265 pages
978-0-12-407202-2 (ISBN)
Description
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
More details
Language
English
Place of publication
Chantilly
United States
Publishing group
Elsevier Science & Techn.
ISBN-13
978-0-12-407202-2 (9780124072022)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Bo Long | Yi Chang
Relevance Ranking for Vertical Search Engines
Book
03/2014
Morgan Kaufmann
€54.46
Shipment within 15-20 days
Persons
Bo Long is currently a staff applied researcher at LinkedIn Inc., and was formerly a senior research scientist at Yahoo! Labs. His research interests lie in data mining and machine learning with applications to web search, recommendation, and social network analysis. He holds eight innovations and has published peer-reviewed papers in top conferences and journals including ICML, KDD, ICDM, AAAI, SDM, CIKM, and KAIS. He has served as reviewer, workshop co-organizer, conference organizer, committee member, and area chair for multiple conferences, including KDD, NIPS, SIGIR, ICML, SDM, CIKM, JSM etc.Dr. Yi Chang is director of sciences in Yahoo Labs, where he leads the search and anti-abuse science group. His research interests include web search, applied machine learning, and social media mining. Yi has published more than 70 conference/journal papers, and he is a co-author of the book, Relevance Ranking for Vertical Search Engines. Yi is an associate editor for Neurocomputing, Pattern Recognition Letters, and he has served as workshops co-organizers, conference organizer committee members, and area chairs for multiple conferences, including WWW, SIGIR, ICML, KDD, CIKM, etc.
Content
1. Introduction2. News Search Ranking3. Medical Domain Search Ranking4. Visual Search Ranking5. Mobile Search Ranking6. Multi-Aspect Relevance Ranking7. Entity Ranking8. Aggregated Vertical Search9. Cross Vertical Search RankingReferences
