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Relevance ranking for vertical search engines / edited by Bo Long, Yi Chang

Published
Amsterdam : Elsevier/Morgan Kaufmann, [2014]
Copyright Date
©2014
Physical Description
1 online resource (xxiii, 239 pages) : illustrations (some color)
Additional Creators
Long, Bo and Chang, Yi (Writer on computers)
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Contents
News search ranking -- Medical domain search ranking -- Visual search ranking -- Mobile search ranking -- Entity ranking -- Multi-aspect relevance ranking -- Aggregated vertical search -- Cross vertical search ranking.
Summary
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 resultsCovers concepts and theories from the fundamental to the advancedDiscusses the state of the art: development of theories and practices in vertical search ranking applicationsIncludes detailed examples, case studies and real-world examples.
Subject(s)
Genre(s)
ISBN
9780124072022 (electronic bk.)
012407202X (electronic bk.)
9781306415439 (electronic bk.)
1306415438 (electronic bk.)
9780124071711
0124071716
Bibliography Note
Includes bibliographical references (pages 201-221) and index.
View MARC record | catkey: 37432267