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Query Selection in Deep Web Crawling: Help your crawler efficiently retrieve data from the largest data sources in the Web - Brossura
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The deep web is the content that is dynamically generated from data sources such as databases or file system. Unlike surface web where web pages are collected by following the hyperlinks embedded inside collected pages, data from a deep web data source is guarded by a search interface and only can be retrieved by queries. The amount of data in deep web exceeds by far that of the surface web. This calls for deep web crawlers to excavate the data so that they can be used, indexed, and searched upon in an integrated environment. Crawling deep web is the process of collecting data from search interfaces by issuing queries. One of the major challenges in crawling deep web is the selection of the queries so that most of the data can be retrieved at a low cost. This work first comprehensively introduces the state-of-art work in query selection techniques for crawling, then in-depth analyzes the remaining problems, such as cold start problem and return limit problem, and finally presents a novel technique to address them.
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L'autore
Yan Wang is an assistant professor of computer science at Central University of Finance and Economics in China. He went on to study computer science at University of Windsor in Canada and received his PhD and Master degrees in 2012 and 2007 respectively. His research interests are in the areas of deep web, online social networks and web analytics.
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Query Selection in Deep Web Crawling: Help your crawler efficiently retrieve data from the largest data sources in the Web
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paperback. Condizione: Very Good. Query Selection in Deep Web Crawling: Help your crawler efficiently retrieve data from the largest data sources in the Web This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. . Codice articolo 7719-9783639712452
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Query Selection in Deep Web Crawling: Help your crawler efficiently retrieve data from the largest data sources in the Web
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Query Selection in Deep Web Crawling
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The deep web is the content that is dynamically generated from data sources such as databases or file system. Unlike surface web where web pages are collected by following the hyperlinks embedded inside collected pages, data from a deep web data source is guarded by a search interface and only can be retrieved by queries. The amount of data in deep web exceeds by far that of the surface web. This calls for deep web crawlers to excavate the data so that they can be used, indexed, and searched upon in an integrated environment. Crawling deep web is the process of collecting data from search interfaces by issuing queries. One of the major challenges in crawling deep web is the selection of the queries so that most of the data can be retrieved at a low cost. This work first comprehensively introduces the state-of-art work in query selection techniques for crawling, then in-depth analyzes the remaining problems, such as cold start problem and return limit problem, and finally presents a novel technique to address them. 152 pp. Englisch. Codice articolo 9783639712452
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Query Selection in Deep Web Crawling : Help your crawler efficiently retrieve data from the largest data sources in the Web
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The deep web is the content that is dynamically generated from data sources such as databases or file system. Unlike surface web where web pages are collected by following the hyperlinks embedded inside collected pages, data from a deep web data source is guarded by a search interface and only can be retrieved by queries. The amount of data in deep web exceeds by far that of the surface web. This calls for deep web crawlers to excavate the data so that they can be used, indexed, and searched upon in an integrated environment. Crawling deep web is the process of collecting data from search interfaces by issuing queries. One of the major challenges in crawling deep web is the selection of the queries so that most of the data can be retrieved at a low cost. This work first comprehensively introduces the state-of-art work in query selection techniques for crawling, then in-depth analyzes the remaining problems, such as cold start problem and return limit problem, and finally presents a novel technique to address them. Codice articolo 9783639712452
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Wang YanYan Wang is an assistant professor of computer science at Central University of Finance and Economics in China. He went on to study computer science at University of Windsor in Canada and received his PhD and Master degrees i. Codice articolo 4999419
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Query Selection in Deep Web Crawling
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The deep web is the content that is dynamically generated from data sources such as databases or file system. Unlike surface web where web pages are collected by following the hyperlinks embedded inside collected pages, data from a deep web data source is guarded by a search interface and only can be retrieved by queries. The amount of data in deep web exceeds by far that of the surface web. This calls for deep web crawlers to excavate the data so that they can be used, indexed, and searched upon in an integrated environment. Crawling deep web is the process of collecting data from search interfaces by issuing queries. One of the major challenges in crawling deep web is the selection of the queries so that most of the data can be retrieved at a low cost. This work first comprehensively introduces the state-of-art work in query selection techniques for crawling, then in-depth analyzes the remaining problems, such as cold start problem and return limit problem, and finally presents a novel technique to address them.OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 152 pp. Englisch. Codice articolo 9783639712452
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