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XML Indexing Techniques for Handling Large Amounts of Data
Objectives: This paper presents an effective XML indexing technology for input/output process and retrieval of large amounts of data to exchange structured documents in the Internet space. Methods/Statistical Analysis: In these days, many data are produce in various forms by Web media, the Internet of Things, and social media. However, the data are too complicated in type and large to effectively analyze, search, and rapid input/output processing with the traditional Relational DB system. In this paper, we have looked to measure the document searching speed, document-writing speed in order to assess the performance of the XML Information Retrieval and management system using an index model. Many cases contain hundreds of millions of different elements of an XML document. In Keyword-based approach, it is necessary for all the elements in the document tagging to a quick search because it does not contain the structural information for the XML document to a query. Findings: The XML is a widely used mark-up language in Internet, and a large amount of data is produce in XML format. In this paper, we propose two search methods for efficient search in a large amount of data with the XML indexing technology. First, existing studies show the true performance to lean to one side in the keyword search of large XML documents have a problem. Both informal and formal data processing, the Content Model was proposes to solve. Non-structured data to a right processing and utilization as NoSQL View in a variety of devices for rapid processing of the user interface was couple to Data. N-Screen or the like can be used without Viewer from various mobile devices, as well as the task of processing that is used in a large variety of services can be advantageous. Improvements: This work can also extended with other searching algorithms for handling large amount of data
Big-Data, Indexing, I/O processing, XML.
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