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Fraud Detection in Web Advertisement

by Sanap Kanchan S., Kuwar Shraddha A., Kulkarni Chinamy U., T.bhaskar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 114 - Number 11
Year of Publication: 2015
Authors: Sanap Kanchan S., Kuwar Shraddha A., Kulkarni Chinamy U., T.bhaskar
10.5120/20024-2058

Sanap Kanchan S., Kuwar Shraddha A., Kulkarni Chinamy U., T.bhaskar . Fraud Detection in Web Advertisement. International Journal of Computer Applications. 114, 11 ( March 2015), 26-29. DOI=10.5120/20024-2058

@article{ 10.5120/20024-2058,
author = { Sanap Kanchan S., Kuwar Shraddha A., Kulkarni Chinamy U., T.bhaskar },
title = { Fraud Detection in Web Advertisement },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 114 },
number = { 11 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 26-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume114/number11/20024-2058/ },
doi = { 10.5120/20024-2058 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:52:30.013761+05:30
%A Sanap Kanchan S.
%A Kuwar Shraddha A.
%A Kulkarni Chinamy U.
%A T.bhaskar
%T Fraud Detection in Web Advertisement
%J International Journal of Computer Applications
%@ 0975-8887
%V 114
%N 11
%P 26-29
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The improvement of the technology and web-based application over the crime and fraud give best result in online advertisement. In recent years fraud is major problem in online advertising. It can affect the trust, beliefs and encouragement of the customer on online marketing. In this thesis, the development of this system can be done using Naive Bayes classifier and Apriori algorithm . The system can find fraud or scam in web based marketing and advertisement . It can also give the solution to the fake advertisement. Main aim of development of this system is public awareness which is very important in today's market

References
  1. Vaibhav Garg and Shirin Nilizadeh, "Craigslist Scams and Community Composition: Investigating online Fraud Victimization". IEEE Transactions on security and privacy workshops year 2013.
  2. Metwally , D. Agrawal ,and A. El Abbadi ," Using Association Rules for Fraud Detection in Web Advertising Network". Technical Report 2005-13, University of california . Santa Barbara, 2005.
  3. Jingnian Chen, Houkuan Huang, Shengfeng Tian, Youli Qu," Feature Selection for text classification with Naïve Bayes", Department of Information and computing Science, Shandong University of finance,Jinan,Shandong,250014,china.
  4. Ishatiq Ahmed, Donghai Guan and Tae choong chang,"SMS classification Based on Naïve Bayes classifier and Apriori Algorithm Frequent Itemset",International Journal of machine Learning and computing, Vol. 4,No. 2,April 2014.
  5. http://www. carwale. com/
  6. http://www. cartrade. com/
  7. http://www. ranks. nl/stopwords
  8. http://adsabs. harvard. edu/abs_doc/stopwords. html
  9. http://tools. seobook. com/general/keyword- density/stop_words. txt
Index Terms

Computer Science
Information Sciences

Keywords

Fraud Naive Bayes Apriori Scam

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