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Reseach Article

Frequent Patterns Analysis using Apriory: A Survey

by Madhavi G. Patil, Ravi P. Patki
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 113 - Number 12
Year of Publication: 2015
Authors: Madhavi G. Patil, Ravi P. Patki
10.5120/19877-1881

Madhavi G. Patil, Ravi P. Patki . Frequent Patterns Analysis using Apriory: A Survey. International Journal of Computer Applications. 113, 12 ( March 2015), 13-16. DOI=10.5120/19877-1881

@article{ 10.5120/19877-1881,
author = { Madhavi G. Patil, Ravi P. Patki },
title = { Frequent Patterns Analysis using Apriory: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 113 },
number = { 12 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 13-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume113/number12/19877-1881/ },
doi = { 10.5120/19877-1881 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:50:44.863510+05:30
%A Madhavi G. Patil
%A Ravi P. Patki
%T Frequent Patterns Analysis using Apriory: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 113
%N 12
%P 13-16
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In applications such as location-based services, natural habitat monitoring, web data integration, and biometric applications, the values of the underlying data are inherently noisy or imprecise. Consider a location-based application that provides querying facilities on geographical objects (e. g. , airports, vehicles, and people) extracted from satellite images. Due to the errors incurred during satellite image transmission, the locations of the geographical objects can be imprecise. The data acquired from the Global Positioning System (GPS) and remote sensors can also be inaccurate and outdated, due to measurement error and network delay. During this paper, this paper tend to propose to live pattern frequentness supported the possible world linguistics. this paper tend to establish 2 unsure sequence information models abstracted from several real-life applications involving uncertain sequence information, and formulate the matter of mining probabilistically frequent serial patterns (or p-FSPs) from information that adapt to developed models. However the amount of attainable worlds is extraordinarily giant, that makes the mining prohibitively expensive. Impressed by the renowned Pre?xSpan algorithmic program, this paper tends to develop 2 new algorithms conjointly referred to as U-Pre?xSpan.

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Index Terms

Computer Science
Information Sciences

Keywords

Frequent patterns uncertain databases approximate algorithm GPS