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- Author: Bo Long
- Publisher: Morgan Kaufmann Publishers
- ISBN-10: 0124071716
- ISBN-13: 9780124071711
- Format: 19.1 x 23.1 x 2 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
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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.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 22d.22:09:01
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Bo Long
- Publisher: Morgan Kaufmann Publishers
- ISBN-10: 0124071716
- ISBN-13: 9780124071711
- Format: 19.1 x 23.1 x 2 cm, minkšti viršeliai
- Language: English 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.
Reviews