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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title: An updated & more efficient algorithm for mining sequential patterns
Authors Name: Krishnakant solanky , Abhishek raghuvanshi
Unique Id: IJSDR1607014
Published In: Volume 1 Issue 7, July-2016
Abstract: Tremendous amount of data being collected is increasing speedily by computerized applications around the world. Hidden in the vast data, the valuable information is attracting researchers of multiple disciplines to study effective approaches to derive useful knowledge from within. Among various data mining objectives, the mining of frequent patterns has been the focus of knowledge discovery in databases. This thesis aims to investigate efficient algorithm for mining including association rules and sequential patterns. Mining sequential patterns with time constraints, such as time gaps and sliding time-window, may reinforce the accuracy of mining results. However, the capabilities to mine the time-constrained patterns were previously available only within Apriori framework. Recent studies indicate that pattern-growth methodology could speed up sequence mining.
Keywords: Mining sequential pattern
Cite Article: "An updated & more efficient algorithm for mining sequential patterns", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.1, Issue 7, page no.67 - 69, July-2016, Available :http://www.ijsdr.org/papers/IJSDR1607014.pdf
Downloads: 000251441
Publication Details: Published Paper ID: IJSDR1607014
Registration ID:160596
Published In: Volume 1 Issue 7, July-2016
DOI (Digital Object Identifier):
Page No: 67 - 69
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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