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Mandoria, H. L.
- Analysis of Pattern Identification Using Graph Database for Fraud Detection
Abstract Views :156 |
PDF Views:4
Authors
Affiliations
1 Department of Information Technology, College of Technology, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar-263145, Uttarakhand, IN
1 Department of Information Technology, College of Technology, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar-263145, Uttarakhand, IN
Source
Oriental Journal of Computer Science and Technology, Vol 9, No 2 (2016), Pagination: 81-91Abstract
Internet is the main tool for e-business. E-transaction is made faster by Internet. With the increase of e-transaction internet fraud or e-business fraud is increasing. Credit fraud in the banking sector is a growing concern. Few sort of card (debit/credit) fraud is decreasing by providing detection and prevention system from banks and government. But card-not-present fraud losses are increasing at higher rate because of online transaction as there is no chance to use Chip and PIN as well as card is not used face-to-face. Card-not-present fraud losses are growing in an un-protective and un-detective way. This paper seeks to investigate the current debate regarding the fraud in the banking sector and vulnerabilities in online banking and to study some possible remedial actions to detect and prevent credit fraud. The research also reveals lots of channels of fraud in online banking which are increasing day by day. These kinds of fraud are the main barriers for the e-business in the banking sector. This paper devised a new approach for fraud detection in these sector with help of graph database&by matching pattern of previous frauds.Keywords
Frauds, Bank Frauds, Online/Offline Frauds, Fraud Detection, Fraud Pattern.References
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- Eichinger F, Böhm K, Huber M. Improved software fault detection with graph mining. In: Appearing in the 6th international workshop on mining and learning with graphs, Helsinki, Finland, 2008.
- Sequeda J, Arenas M, Miranker DP. On directly mapping relational databases to RDF and OWL. In WWW, pp. 49-58, 2012.
- Kashyap N.K., “Evaluation of Proposed Algorithm with Preceding GMT for Fraudulence Diagnosis”. Orient.J. Comp. Sci. and Technol; 9(2). Available from:http://www.computerscijournal.org/?p=3661
- Navneet Kumar Kashyap, Binay Kumar Pandey, H. L. Mandoria & Ashok Kumar,”A Comprehensive Study Of Various Kinds Of Frauds & It’s Impact”, International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR) ISSN(P): 2249-6831; ISSN(E): 2249-7943 Vol. 6, Issue 3, Jun 2016, 47-58,
- Navneet Kumar Kashyap, Binay Kumar Pandey, H. L. Mandoria & Ashok Kumar, “A Review Of Leading Database: Relational & Non-Relational Database”, I-Manager’s Journal On Information Technology (JIT) ISSN (P): 2277-5110; ISSN (E): 2277-5250, (Accepted On May 31, 2016)
- Navneet Kumar Kashyap, Binay Kumar Pandey, H. L. Mandoria & Ashok Kumar, “Comprehensive Study of Different Pattern Recognition Techniques”, i-manager’s Journal on Pattern Recognition (JPR)ISSN(P): 2349-7912; ISSN(E): 2350-112X, vol. 2, No. 4, 42-49 ( Accepted on JUNE 9, 2016)
- Navneet Kumar Kashyap, Binay Kumar Pandey, H. L. Mandoria & Ashok Kumar, “GRAPH MINING USING gSpan: GRAPH BASED SUBSTRUTURE PATTERN MINING”, International Journal of Applied Research on Information Technology and Computing (IJARITAC), ISSN(P):0975-8070; ISSN(E): 0975-8089, Vol. 7, No. 2, August 2016 ,( Accepted on JUNE 13, 2016).
- Text Localization and Extraction from Still Images using Fast Bounding Box Algorithm
Abstract Views :149 |
PDF Views:2
Authors
Affiliations
1 Department of Information Technology, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, IN
1 Department of Information Technology, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, IN
Source
Oriental Journal of Computer Science and Technology, Vol 9, No 2 (2016), Pagination: 104-108Abstract
Text Extraction and Localization from images is a very challenging task because of noise, blurriness and complex color background of the images. Digital Images are subjected to blurring due to many hardware limitations such as atmospheric disturbance, device noise and poor focus quality. In order to remove textual information from images it is necessary to remove blurriness and restore the image for the text extraction. Thus in this paper Fast Bounding Box algorithm is applied for localization and extraction of the text from images in an efficient manner by dividing the image into two halves and then find the dissimilar region i.e. text.Keywords
Fast Bounding Box, ROI, Bhattacharya Coefficient, Precision, Recall and F-Measure.References
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- Study and Analysis of Multilingual Hand Written Characters Recognition Using SVM Classifier
Abstract Views :156 |
PDF Views:7
Authors
Affiliations
1 Department of Information Technology, G. B. Pant University of Agriculture and Technology, Pantnagar, IN
1 Department of Information Technology, G. B. Pant University of Agriculture and Technology, Pantnagar, IN
Source
Oriental Journal of Computer Science and Technology, Vol 9, No 2 (2016), Pagination: 109-114Abstract
Day by day the researchers are trying to make such characters recognition system that can be able to detect the writing and languages of individuals, for this multilingual handwritten characters recognition is such system that playing a vital role for recognizing the characters written in different languages and in different styles. The research work presented in this thesis aims to do the study and analysis to recognize the multilingual handwritten characters with a high level of accuracy and for this purpose the classifier that we are using is support vector machine. Here in this work we have used the languages like Hindi and English and along with this we have taken special characters and numerals and tried to recognize them with our system.Keywords
OCR, Handwritten Characters,Recognition,SVM.References
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- Arya, S., C., Singh, R., S. and Mandoria, H., L. 2015. Image Denoising in Hand Written Document for Degraded Documents using Wiener Filter Algorithm.International Journal for Research in Emerging Science and Technology, 2, 7.
- Bansal, C. and Khan, A. 2014. Handwritten numeral recognition using svm and chain code,IJARET, 2: VII.
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- Vohra,U.S.,Dwivedi, S.P., Mandoria, H.L.2016. An analytical study of handwritten character recognition.i-manager’s Journal on Pattern Recognition, 2, 4.
- SonalPaliwal, Rajesh Shyam Singh & H. L. Mandoria. A survey on various text detection and extraction techniques from videos and images.International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR). 6, 3, 1-10.