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DC Field | Value | Language |
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dc.contributor.author | Verma, Jai Prakash | - |
dc.contributor.author | Mankad, Sapan H. | - |
dc.date.accessioned | 2012-01-28T08:40:25Z | - |
dc.date.available | 2012-01-28T08:40:25Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | Proceedings of the International Conference on Advanced Computing and Communication Technologies (ACCT 2011) Page No. 63-66 | en_US |
dc.identifier.uri | http://10.1.7.181:1900/jspui/123456789/2794 | - |
dc.description.abstract | Smart Inbox - this concept has recently been in demand due to well developing era of data analysis so as to make it comfortable for future prediction. Statistical Learning and Data Mining are the fields which are growing rapidly and have started capturing the attention of many of the business organizations to ease their work with the help of classification and prediction.In this paper,we have made an effort to use one of the classification methods, Bayesian Learning to categorize the incoming mails to a specific mail recipient. It uses the available knowledge to classify the training data and then predicts the status of the new incoming mail. We compare the formula based analytical result with that obtained through algorithms supported by Weka tool and suggest the most suitable way to use bayesian technique. | en_US |
dc.publisher | RG Education Society | en_US |
dc.relation.ispartofseries | ITFCA007-2 | en_US |
dc.subject | Computer Faculty Paper | en_US |
dc.subject | Faculty Paper | en_US |
dc.subject | ITFCA007 | en_US |
dc.subject | ITFIT008 | en_US |
dc.title | Smart Inbox : A comparison based Approach to Classify the Incoming Mails | en_US |
dc.type | Faculty Papers | en_US |
Appears in Collections: | Faculty Papers, CE |
Files in This Item:
File | Description | Size | Format | |
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ITFCA007-2.pdf | ITFCA007-2 | 191.57 kB | Adobe PDF | ![]() View/Open |
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