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Using Green Computing Resources to find Fraud Mobile Apps Based Reviews and Ratings

A. Lakshmi1 , N.V. Devi2

Section:Review Paper, Product Type: Journal Paper
Volume-4 , Issue-10 , Page no. 157-160, Oct-2016

Online published on Oct 28, 2016

Copyright © A. Lakshmi, N.V. Devi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: A. Lakshmi, N.V. Devi, “Using Green Computing Resources to find Fraud Mobile Apps Based Reviews and Ratings,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.157-160, 2016.

MLA Style Citation: A. Lakshmi, N.V. Devi "Using Green Computing Resources to find Fraud Mobile Apps Based Reviews and Ratings." International Journal of Computer Sciences and Engineering 4.10 (2016): 157-160.

APA Style Citation: A. Lakshmi, N.V. Devi, (2016). Using Green Computing Resources to find Fraud Mobile Apps Based Reviews and Ratings. International Journal of Computer Sciences and Engineering, 4(10), 157-160.

BibTex Style Citation:
@article{Lakshmi_2016,
author = {A. Lakshmi, N.V. Devi},
title = {Using Green Computing Resources to find Fraud Mobile Apps Based Reviews and Ratings},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2016},
volume = {4},
Issue = {10},
month = {10},
year = {2016},
issn = {2347-2693},
pages = {157-160},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1160},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1160
TI - Using Green Computing Resources to find Fraud Mobile Apps Based Reviews and Ratings
T2 - International Journal of Computer Sciences and Engineering
AU - A. Lakshmi, N.V. Devi
PY - 2016
DA - 2016/10/28
PB - IJCSE, Indore, INDIA
SP - 157-160
IS - 10
VL - 4
SN - 2347-2693
ER -

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Abstract

The model of Green Computing (GC) is gaining increasing popularly extent in the preceding years. GC is a dynamic research extent which studies proficient use of calculating resource. We apply the GC concept in mobile app development to decrease the time & find scam apps from the app store. The Mobile App is a very widely held and well-known concept due to the fast development in the portable technology. In this concept, we are proposing two enhancements. First of all, utilizing endorsement of scores by the administrator to recognize the correct surveys and rating scores. Next, by a same individual for pushing up that application on the pioneer board are confined. Two different constraints are considered for accepting the feedback given to an application. We are likewise contributing the three kinds of proofs: Ranking grounded confirmation, Rating grounded proof and Review grounded proof. In addition, we propose an enhancement grounded application to incorporate every one of the confirmations for extortion recognition in light of EIRQ (Efficient Information Retrieval for Ranked Query) calculation utilizing GC. Finally, the proposed technique will be assessed with genuine App information which is to be gathered from the App Store for quite a while period.

Key-Words / Index Term

Mobile Apps, Ranking scam Detection, Green Computing, Rating nd Review

References

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