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ISBN: 012407202X 0124071716 1306415438 9780124072022 9781306415439 9780124071711 Year: 2014 Publisher: Amsterdam : Morgan Kaufmann, an imprint of Elsevier,
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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
Text processing (Computer science) --- Sorting (Electronic computers) --- Relevance --- Database searching --- Search engines --- Engineering & Applied Sciences --- Computer Science --- Programming --- Relevance. --- Database searching. --- Programming. --- Computer programming --- Data base searching --- Database search strategies --- Search strategies in databases --- Searching databases --- Electronic information resource searching --- Pertinence --- Relevancy --- Meaning (Philosophy) --- Meaning (Psychology) --- Computer sorting --- Electronic data processing --- Processing, Text (Computer science) --- Database management --- Information storage and retrieval systems --- Word processing
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ISBN: 9780124072022 012407202X 9781306415439 1306415438 Year: 2014 Publisher: Amsterdam Elsevier/Morgan Kaufmann
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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.
Book
ISBN: 1450315550 Year: 2012 Publisher: [Place of publication not identified] ACM
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ISBN: 9781638281436 1638281432 Year: 2023 Publisher: Norwell, MA : Now Publishers,
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This is the first comprehensive overview of Graph Neural Networks for Natural Language Processing. It provides students and researchers with a concise and accessible resource to quickly get up to speed with an important area of machine learning research.
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