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ISSN: 2321-9939 | ESTD Year: 2013

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Paper Title
Data Mining For Intensional Query Answering Using Tree Based Association Rules
  Neha H. Nasre,  Kapil Hande

Enormous amount of data on internet contains huge amount of structured and unstructured formats of data. As the amount of data on internet is growing, so it is a difficult task to extract the information from the semi-structured documents. The datasets returned as answer to queries are also unable to convey the interpretable knowledge. Here, in this work, Tree Based Association Rules (TARs) are used to provide the approximate and intensional knowledge about the structure and contents of the XML Documents. This intensional knowledge can be further be used to provide the idea of the structure and contents of the XML document and to provide the approximate answer to the user queries in less time.

Keywords- Extensible Markup Language (XML), intensional knowledge, Tree Based Association Rules (TARs)
Publication Details
Unique Identification Number - IJEDR1602181
Page Number(s) - 1037-1040
Pubished in - Volume 4 | Issue 2 | May 2016
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Neha H. Nasre,  Kapil Hande,   "Data Mining For Intensional Query Answering Using Tree Based Association Rules", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 2, pp.1037-1040, May 2016, Available at :http://www.ijedr.org/papers/IJEDR1602181.pdf
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