Extracting Information from Semistructured Xml Using Tars
R.Sree Lekshmi1, B. Sasi kumar2
1R.Sree Lekshmi, Dept. of Computer Science & Engineering. The Rajas Engineering College, Vadakangulam, India.
2B. Sasi kumar, Professor, Dept of Computer Science The Rajas Engineering College, Vadakangulam. India.
Manuscript received on September 25, 2012. | Revised Manuscript received on October 09, 2012. | Manuscript published on October 30, 2012. | PP: 17-19 | Volume-2 Issue-1, October 2012. | Retrieval Number: A0743102112/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Extracting information from semi structured documents is a very hard task, and is going to become more and more critical as the amount of digital information available on the internet grows. Indeed, documents are often so large that the dataset returned as answer to a query may be too big to convey interpretable knowledge. This work describe an approach based on Tree-based Association Rules (TARs) mined rules, which provide approximate, intentional information on both the structure and the contents of XML documents. This mined knowledge is used to provide: structure and the content of the XML document and quick, approximate answers to queries.
Keywords: XML, approximate query-answering, data mining, intensional information, succinct answers.