Implementation of Information Retrieval (IR) in an Electronic Commerce Architecture using Back Propagation Network Learning (BPNL) Algorithm

Implementation of Information Retrieval (IR) in an Electronic Commerce Architecture using Back Propagation Network Learning (BPNL) AlgorithmRiktesh Srivastava, PhDWhat the Research is all about?

Amazing Factors-Electronic Commerce

Trend is decreasing

Why the trend is decreasing?Slow performance of the E-Commerce Architecture 12.32%People are unable to find suitable E-Commerce locations 37%People unable to find suitable products on E-Commerce locations-51.63%

People unable to find suitable products on E-Commerce locations-51.63% - Is there any solution?

Electronic Commerce Architecture B2C EC

B2C-ANN Architecture

ANN Architecture-In Detail

ANN Architecture-In DetailRequests Received at Input LayerHidden LayerAt this juncture, the requests needs to be searched from DB ServerUses some weight for the requests received at the Input LayerOutput LayerAdditional Weights from Hidden and Output Layer and Process the Information Activation FunctionRepetitionBPNL AlgorithmInitialize weights for the request type (small random numbers) For each training of user requests Repeat until weights convergence or till a required number of epochs are completed Receive requests as it will be extracted from various queues Propagate the error backward from output layer to hidden and input layer. Calculate new weights in accordance with BPNL algorithm. Replace old weights new weights as taken from training algorithm After every t time units Measure performance of each requests Repeat until performance falls below a threshold level() else go to Step iv. Set activation of input unit. Inputs to input layer will be actual packets that are to be scheduled. Compute output of hidden and output layer using sigmoid activation function Output will be fed to weight decider module which will calculate the required change in weights of the queues.

Research Outcomes

Results

RecommendationsImplementation of BPNL Algorithm at the DB server level increases the performance of the system Decreases the Response time of the systemAims to implement the code for a test B2C EC Architecture and evaluate the performance for other EC Architecture as well.