REAL TIME PROJECT !! "REDUNDANT WALL SCANNING" IN THENI ALLINAGARAM

In this Application, system is to scan undesired messages from Redundant walls. The system exploits a ML soft classifier to enforce customizable contentdependent FRs.Moreover, the flexibility of the system in terms of scanning options is enhanced through the management of BLs.This work is the first step of a wider project. The early encouraging results we have obtained on the classification procedure prompt us to continue with other work that will aim to improve the quality of classification. In particular,future plans contemplate a deeper investigation on two interdependent tasks. The first concerns the extraction and/ or selection of contextual features that have been shown to have a high discriminative power. The second task involves the learning phase. Since the underlying domain is dynamically changing, the collection of preclassified data may not be representative in the longer term. The present batch learning strategy, based on the preliminary collection of the entire set of labeled data from experts, allowed an accurate experimental evaluation but needs to be evolved to include new operational requirements. In future work, we plan to address this problem by investigating the use of online learning paradigms able to include label feedbacks from users. Additionally, we plan to enhance our system with a more sophisticated approach to decide when a user should be inserted into a BL contact for more information: