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Survey on Data-intensive Applications, Tools and Techniques for Mining Unstructured Data

by Santhosh Voruganti
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 146 - Number 12
Year of Publication: 2016
Authors: Santhosh Voruganti
10.5120/ijca2016910946

Santhosh Voruganti . Survey on Data-intensive Applications, Tools and Techniques for Mining Unstructured Data. International Journal of Computer Applications. 146, 12 ( Jul 2016), 23-27. DOI=10.5120/ijca2016910946

@article{ 10.5120/ijca2016910946,
author = { Santhosh Voruganti },
title = { Survey on Data-intensive Applications, Tools and Techniques for Mining Unstructured Data },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 146 },
number = { 12 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume146/number12/25451-2016910946/ },
doi = { 10.5120/ijca2016910946 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:50:16.364506+05:30
%A Santhosh Voruganti
%T Survey on Data-intensive Applications, Tools and Techniques for Mining Unstructured Data
%J International Journal of Computer Applications
%@ 0975-8887
%V 146
%N 12
%P 23-27
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Due to the swift growth of WWW there has been large volume of information is produced and shared by various administrations in nearly every business, industry and other fields. Due to this high explosion it’s really a big challenge to store, manage and access knowledge. Experts estimate that 80 to 90 percent of the data in any organization is unstructured. And the amount of unstructured data in enterprises is growing significantly. Often many times faster than structured databases .Unstructured data files often include text and multimedia content. Examples include e-mail messages, word processing documents, pdfs ,videos, photos, audio files, presentations, web pages and many other kinds of business documents. A huge amount of information spread across the web poses a major challenge in identifying relevant information. Existing tools lack analysis and visualization capabilities and traditional result displays long list of documents instead of providing concrete answers. This paper discusses various methods,tools and techniques for mining unstructured data that enables better data analysis and visualization.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Unstructured data structured data data mining text mining machine learning DGE model.

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