Artículos relacionados a Relevance Ranking for Vertical Search Engines

Relevance Ranking for Vertical Search Engines - Tapa blanda

Long, Bo

 
9780124071711: Relevance Ranking for Vertical Search Engines
Tapa blanda
ISBN 10: 0124071716 ISBN 13: 9780124071711
Editorial: Morgan Kaufmann, 2014

Sinopsis

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.

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Acerca de los autores

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.

De la contraportada

In plain, uncomplicated language, using detailed examples to explain the key concepts, models and algorithms in vertical search ranking, Relevance Ranking of Vertical Search Engines teaches readers how to manipulate ranking algorithms to achieve better results in real world applications. A reference book for professionals, the book covers concepts and theories from the very fundamental to the advanced, such as relevance, query intention, location-based relevance, ranking and cross-property ranking. It covers the most recent development of theories and practices 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 the applications involving multiple verticals.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Morgan Kaufmann
Año de publicación
2014
Idioma
Inglés
ISBN 10 
0124071716
ISBN 13 
9780124071711
Encuadernación
Tapa blanda
Número de páginas
264
Contacto del fabricante
no disponible
Persona responsable
gpsr@libri.de
gpsr@libri.de

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