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Content-oriented XML retrieval has been receiving increasing interest due to the widespread use of eXtensible Markup Language (XML), which is becoming a standard document format on the Web, in digital libraries,and publishing. By exploiting the enriched source of syntactic and semantic information that XML markup provides, XML information retrieval (IR) systems aim to implement a more focused retrieval strategy and return document components, so-called XML elements – instead of complete documents – in response to a user query. This focused retrieval approach is of particular bene?t for collections containing long documents or documents covering a wide variety of topics (e.g., books, user manuals, legal documents, etc.), where users’ e?ort to locate relevant content can be reduced by directing them to the most relevant parts of the documents. Implementing this, more focused, retrieval paradigm means that an XML IR system needs not only to ?nd relevant information in the XML documents, but it also has to determine the appropriate level of granularity to be returned to the user. In addition, the relevance of a retrieved component may be dependent on meeting both content and structural query conditions.
Extensible Markup Language (XML) NLP XML XML data retrieval XML retrieval relevance ranking database digital libraries information retrieval interactive XML information retrieval metadata multimedia natural language processing query processing relational database
Springer-Verlag Berlin Heidelberg 2006
Springer, Berlin, Heidelberg
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