1. CSE591: Data Mining by H. Liu
XML and RDF
Reference 1: Webmaster in a Nutshell
Reference 2: A Query Language for XML
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CSE591: Data Mining by H. Liu

2. Extensible Markup Language
A document processing standard proposed by W3C
A simplified form of SGML (standard generalized)
The ML of choice for dynamically generated content
A meta-language to create and format one’s own document markups.
With HTML, existing markup is static, can’t be changed or extended
With XML, you can create your own markup tags and configure each to your liking.
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CSE591: Data Mining by H. Liu

3. CSE591: Data Mining by H. Liu
XML terms
An element with two tags
<Class>This is CSE591</Class>
Elements can have attributes
<Class level=“graduate”>CSE591</Class>
Empty elements are often used to add nontextual content
<Picture src=“ASU-Campus.gif”/>
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CSE591: Data Mining by H. Liu

4. CSE591: Data Mining by H. Liu
An XML document
Three files are processed by an XML-compliant application to display XML content
The file contains document data tagged with meaningful XML elements
A stylesheet dictates how document elements should be formatted when they are displayed (the separation between content and formatting)
Document type definition (DTD) specifies rules for how XML elements, attributes, and other data are defined and logically related
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CSE591: Data Mining by H. Liu

5. CSE591: Data Mining by H. Liu
Well-formed XML
The document must either use a DTD or contain an XML declaration with the standalone attribute set to “no”. E.g.,
<?xml version=“1.0” standalone=“no”?>
Well-formed XML documents w/o a DTD must have all attributes of type CDATA by default
Valid XML
if it adheres to the specifications outlined by its DTD
Occurrence operators (?, +, *)
Xlink and Xpointer
support inter-document linking and provide a way of referring to data from multiple sources in one XML document
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CSE591: Data Mining by H. Liu

6. CSE591: Data Mining by H. Liu
A simple XML document
Basic components
XML declaration <?xml … ?>
root element <!DOCTYPE name SYSTEM “some.dtd”>
comment <!-- you can put a comment here -->
namespace (xmlns): each element tag could have two parts separated by “A:B”. “A” forms the tag’s namespace, “B” identifies the name of the tag
A simple example (Example 10-1, p128)
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CSE591: Data Mining by H. Liu

7. CSE591: Data Mining by H. Liu
A simple DTD
Basic components
<!-- DTD for some document -->
<!ELEMENT …> construct declares each valid element for the document
A simple example (Example 10-2, p130)
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CSE591: Data Mining by H. Liu

8. CSE591: Data Mining by H. Liu
Data types
ANY - both other tags and general CDATA
PCDATA - parsed character data
CDATA - character data (by default if w/o DTD)
NDATA - notation data
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CSE591: Data Mining by H. Liu

9. Resource Description Framework
RDF provides a standard framework for describing resource metadata (info about info)
As such, it is important for the future development of search engines and other web navigation applications
Netscape’s Meta Content Framework - tracking info about Web sites
The Platform for Internet Content Selection - filtering inappropriate material based on external descriptions of content
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CSE591: Data Mining by H. Liu

10. CSE591: Data Mining by H. Liu
Web Data and EDI
Electronic data interchange
One important application of XML is EDI between two or more data sources on the Web
E.g., search bots could integrate automatically information from related sources that published in XML
EDI applications require tools that support:
extraction of data from large XML documents
conversion of data between relational or OO DBs and XML data
transformation of data from one DTD to another DTD
integration of multiple XML data sources
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CSE591: Data Mining by H. Liu

11. CSE591: Data Mining by H. Liu
XML-QL
Query languages
solutions to data extraction, conversion, transformation, and integration
Why not adapt SQL or OQL to querying XML
XML is not rigidly structured
Schema information is stored with data in XML
XML data can naturally model irregularities that cannot be modeled by relational or object-oriented data
flexibility to accommodate all the irregularities is crucial for EDI applications
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CSE591: Data Mining by H. Liu

12. CSE591: Data Mining by H. Liu
Examples in XML-QL
Matching data using element patterns
Constructing XML data
Prototype of XML-QL can be found at
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CSE591: Data Mining by H. Liu