This page contains some suggested use-cases for WikiXMLDB.

Ask sophisticated queries against Wikipedia content

Wikipedia search facilities avaliable at wikipedia.org are limited to full-text search only. WikiXMLDB supports W3C XQuery Language and allows you to:

• Formulate powerful database-like queries over the structure and values of Wikipedia content. For example, you can retrieve all links from the 'See also' section and include their abstracts. Or you can find all US born scientists who got a Turing Award (this information is available in the infoboxes of the articles).
• Combine full-text and structural queries. For example, you can find all articles which include 'XQuery' keyword and are in the 'Database management systems' category.
• XQuery is not just a language for querying, it also provides facilities to create XML documents on the fly, based on search results. This allows you to combine pieces of Wikipedia content coming from various articles into a single xml document. For example you can compound an XML document that contains summaries of commercial text mining tools. You can publish this document into HTML using XSLT (or even XQuery itself: XHTML is an XML format and is recognized by web browsers).

Enrich your Web site with Wikipedia

Wikipedia is a valuable resource that can be used to enrich your content. For example, you can enrich your Web site with information retrieved from Wikipedia such as lists of 'UK Club DJs' if your site is about modern UK music. This information will stay up-to-date as Wikipedia changes. Another example is to integrate Wikipedia content with your geographic data as Wikipedia contains more then 300,000 geographic locations with their geo-coordinates.

Improve your Natural Language Processing, Text Mining and other tools

Wikipedia is one of the largest multi-domain knowlegde base that currently exist. Using information from Wikipedia will allow you to improve your information processing applications in various ways. For example you can use Wikipedia as an advanced up-to-date dictionary that includes a lot of named entities. You can use redirection articles of Wikipedia to create a dictionary of synonyms. Wikipedia also contains disambiguation pages that list various meaning of ambiguous words, this information is invaluable in some NLP applications.

If you have any other ideas on use cases, please email us at modis@ispras.ru.