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Mining Multiple Text Sequence with Key Management

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 90 - Number 2
Year of Publication: 2014
G. V Sam Kumar
A. Angel Princes
R. Karthiga
T. Rajesh

Sam G V Kumar, Angel A Princes, R Karthiga and T Rajesh. Article: Mining Multiple Text Sequence with Key Management. International Journal of Computer Applications 90(2):32-36, March 2014. Full text available. BibTeX

	author = {G. V Sam Kumar and A. Angel Princes and R. Karthiga and T. Rajesh},
	title = {Article: Mining Multiple Text Sequence with Key Management},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {90},
	number = {2},
	pages = {32-36},
	month = {March},
	note = {Full text available}


A Text stream is a sequence of chronologically ordered documents, being generated in various forms. Multiple text streams that are correlated to each other by sharing common topics. Our aim is to extract the knowledge of the text stream from the listed documents. In particular, vulnerabilities could include compromise of data security and loss of information which leads to data leakage. To provide a data security and privacy a key management is used. Documents from different sequences about the same topic may have different time stamps termed as asynchronous. Here we first, us e Apriori Algorithm to extract the common topics for the search text from the given data set based on the time stamps using Timestamp-Based Protocols. We also use vormetric encryption algorithm, which combines Encryption and integrated key management to protect and control access to sensitive files on file servers. Second, Ranking is involved in both admin side and user side of mining work which is based on usability of documents.


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