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A Methodology for the Usage of Side Data in Content Mining

by Solunke B.R., Priyanka S. Muttur, Amol U. Kuntham, Seema S.chavan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 112 - Number 6
Year of Publication: 2015
Authors: Solunke B.R., Priyanka S. Muttur, Amol U. Kuntham, Seema S.chavan
10.5120/19667-1101

Solunke B.R., Priyanka S. Muttur, Amol U. Kuntham, Seema S.chavan . A Methodology for the Usage of Side Data in Content Mining. International Journal of Computer Applications. 112, 6 ( February 2015), 1-8. DOI=10.5120/19667-1101

@article{ 10.5120/19667-1101,
author = { Solunke B.R., Priyanka S. Muttur, Amol U. Kuntham, Seema S.chavan },
title = { A Methodology for the Usage of Side Data in Content Mining },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 112 },
number = { 6 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume112/number6/19667-1101/ },
doi = { 10.5120/19667-1101 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:48:42.057355+05:30
%A Solunke B.R.
%A Priyanka S. Muttur
%A Amol U. Kuntham
%A Seema S.chavan
%T A Methodology for the Usage of Side Data in Content Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 112
%N 6
%P 1-8
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Compelling In different text mining applications, side-information is accessible close-by the text records. Such side-information may be of distinctive sorts, case in point, report provenance information, the relationship in the record, client access conduct from web logs, or other non-textual properties which are embedded into the text document. Such qualities may contain a monster measure of information for clustering purposes. On the other hand, the relative targets of this side-information may be hard to gage, particularly precisely when a portion of the information is uproarious. In such cases, it can be dangerous to unite side-information into the mining logic, in light of the way that it can either redesign the method for the representation for the mining process, or can add unsettling influence to the system. Subsequently, we oblige a principled strategy to perform the mining system, to build the slant from utilizing this side information. In this paper, we mastermind a processing which joins secured disseminating with probabilistic models so as to make a persuading social occasion method. We then show to broaden the methodology to the approach issue. We show test happens on different true blue information sets to design the focal purposes of utilizing such a method.

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Index Terms

Computer Science
Information Sciences

Keywords

Clustering Data mining Text mining.

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