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Feed Optimization System based on Quality Filtering

by Ritika Nevatia, Soham Kanade, Yashaswi Alladi, Chintan Panchamia, Kiran Gawande
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 106 - Number 1
Year of Publication: 2014
Authors: Ritika Nevatia, Soham Kanade, Yashaswi Alladi, Chintan Panchamia, Kiran Gawande
10.5120/18482-9539

Ritika Nevatia, Soham Kanade, Yashaswi Alladi, Chintan Panchamia, Kiran Gawande . Feed Optimization System based on Quality Filtering. International Journal of Computer Applications. 106, 1 ( November 2014), 6-11. DOI=10.5120/18482-9539

@article{ 10.5120/18482-9539,
author = { Ritika Nevatia, Soham Kanade, Yashaswi Alladi, Chintan Panchamia, Kiran Gawande },
title = { Feed Optimization System based on Quality Filtering },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 106 },
number = { 1 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 6-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume106/number1/18482-9539/ },
doi = { 10.5120/18482-9539 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:38:13.799996+05:30
%A Ritika Nevatia
%A Soham Kanade
%A Yashaswi Alladi
%A Chintan Panchamia
%A Kiran Gawande
%T Feed Optimization System based on Quality Filtering
%J International Journal of Computer Applications
%@ 0975-8887
%V 106
%N 1
%P 6-11
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The phenomenal rate at which data is being generated on social networking websites demands for effective organization and administration methods. The current approach leads to loss of quality content amongst popular content. The paper presents an algorithm that ranks content in an ecosystem according to quality relevance to generate an organized and improved feed which evolves with the changes in data. For achieving relevance of content, the algorithm considers different parameters like user interests, article category, domain expertise of a user, quality rating of an article, and its future popularity and user activities in the ecosystem. These attributes are normalized according to the extent of their effect in determining the overall rank of an article.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Domain expertise Quality filtering Personalizing Content ranking Web feed optimization Algorithm User interaction Social media

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