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Storage and Retrieval of XML Documents with a Cluster of Database Systems by T. Grabs (2003, Trade Paperback)

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About this product

Product Identifiers

PublisheriOS Press, Incorporated

ISBN-101586033719

ISBN-139781586033712

eBay Product ID (ePID)5960006

Product Key Features

Number of Pages250 Pages

Publication NameStorage and Retrieval of Xml Documents with a Cluster of Database Systems

LanguageEnglish

Publication Year2003

SubjectComputer Science

TypeTextbook

AuthorT. Grabs

Subject AreaComputers

FormatTrade Paperback

Dimensions

Item Weight12 Oz

Item Length7.9 in

Item Width5.9 in

Additional Product Features

Intended AudienceScholarly & Professional

Volume NumberVol. 82

SynopsisXML - short for the W3C eXtended Markup Language - is highly successful as a format for data interchange. So far, the focus with XML has been on data-centric settings, i.e., XML documents with strict and regular structure. However, this disregards many important settings that require textual or semi-structured data with little or flexible structure. XML, however, is flexible enough to cover these so-called document-centric settings in addition to data-centric ones. This book presents an XML engine for storage and retrieval of XML documents which covers the full range from data-centric to document-centric applications on a single integrated platform. It proposes to extend data-centric XML query languages such as W3C XPath with document-centric functionality needed for relevance-oriented ranked retrieval on XML documents. Moreover, it investigates transaction management for concurrent XML processing and contributes a novel locking protocol that allows for higher concurrency and more parallelism than off-the-shelf database transaction management. To make XML storage and retrieval efficient and highly scalable, both data-centric and document-centric XML contents are stored on a cluster of relational database systems. The overall result is a scalable infrastructure for storage and retrieval of XML documents with up-to-date retrieval results supporting state-of-the-art ranked retrieval models.