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Intelligent XML Query-Answering Support with Efficiently Updating XML Data in Data Mining

Parag Zaware, Prabhudev.I,

Affiliations
Vishwabharati Academy College of Engineering, Ahmednagar
:10.22362/ijcert/2016/v3/i12/xxxx


Abstract
Data is present in various unstructured format. Extracting information from non structured documents is a very difficult task and it is become more and more critical when the amount of digital information available over the internet increases. This paper is based on design of Branch Organization Rule (BOR) results in approximate answer of queries for mining. XML is popular portable language best suitable for many web technologies hence we prefer XML. While implementing XML Query Answering we are going to implement Naïve Bayes as Machine learning algorithm which we will use specially for Query Classification. We are also implementing same concept for rules classifications by using which the trees are generated after applying queries. Due to creating classification of queries our accuracy of results will increase.


Citation
Parag Zaware,Prabhudev.I," Intelligent XML Query-Answering Support with Efficiently Updating XML Data in Data Mining”, International Journal Of Computer Engineering In Research Trends, 3(12):613-619,December-2016.


Keywords : XML, Mining, query answer, Machine Learning.

References
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