In the new semester, our Lab, Web Search Mining and Security Lab, plans to hold an academic seminar every Wednesdays, and each time a keynote speaker will share understanding of papers published in recent years with you.
This week’s seminar is organized as follows: 1. The seminar time is 1.pm, Wed., at Zhongguancun Technology Park ,Building 5, 1306. 2. The lecturer is Yvette, the paper’s title is Curriculum Learning for Natural Answer Generation. 3. The seminar will be hosted by Baohua Zhang. 4. Attachment is the paper of this seminar, please download in advance.
Anyone interested in this topic is welcomed to join us. the following is the abstract for this week’s paper.
Credit Card Fraud Detection using Non-Overlapped Risk based Bagging
S. Akila U. Srinivasulu Reddy
Fraud due to credit card misuse costs
consumers several billions of dollars annually. This is due to the huge usage
levels and inability of the systems to automatically detect the anomalies. This
paper analyzes the implicit nature of data with noise and imbalance and
proposes a Non-overlapped Risk based Bagged Ensemble model (NRBE) to handle
imbalance and noise contained in the credit card transactions. The bagging
model has been enhanced in terms of a novel bag creation model and an effective
risk based base learner. Non-overlapped bag creation generates training subsets
to handle data imbalance and the risk based Na?ve Bayes eliminates the issues
arising due to noise. Experiments were conducted and comparisons were performed
with existing state-of-the-art fraud detection models, which indicates that
NRBE exhibits improved performances of 5% in terms of BCR and BER, 50% in terms
of Recall and 2X to 2.5X times reduced cost.