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XML language – Because it is an XML language, only an XSLT transform (and an XSLT processor) is required to generate XSL-FO code from any XML language. One can easily write a document in TEI or DocBook, and transform it into HTML for web viewing or PDF (through an FO processor) for printing. In fact, there are many pre-existing TEI and ...
In order for a web browser to be able to apply an XSL transformation to an XML document on display, an XML stylesheet processing instruction can be inserted into XML. So, for example, if the stylesheet in Example 2 above were available as "example2.xsl", the following instruction could be added to the original incoming XML: [ 25 ]
You can also use regular expressions to directly process parts of the XML code. These run fast but are difficult to maintain. Please list methods and tools for processing XML export here: Parse::MediaWikiDump is a perl module for processing the XML dump file. m:Processing MediaWiki XML with STX - Stream based XML transformation
^ XML data bindings and SOAP serialization tools provide type-safe XML serialization of programming data structures into XML. Shown are XML values that can be placed in XML elements and attributes. ^ This syntax is not compatible with the Internet-Draft, but is used by some dialects of Lisp.
XML Data Package (XDP) is an XML file format created by Adobe Systems in 2003. It is intended to be an XML-based companion to PDF. It allows PDF content and/or Adobe XML Forms Architecture (XFA) resources to be packaged within an XML container. Several products by Adobe, most notably its LiveCycle ES Suite, use files in XDP format. XDP is XML 1 ...
Beautiful Soup is a Python package for parsing HTML and XML documents, including those with malformed markup. It creates a parse tree for documents that can be used to extract data from HTML, [3] which is useful for web scraping. [2] [4]
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Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points.