Multi-Document Based Text Summarization Through Deep Learning Algorithm

The proposed approach is provided an effort in terms of deep leaning algorithm to retrieve an effective text summary for a set of documents by exploiting three different algorithms to make the text summarisation process an effective one.

Abstract

The proposed approach is provided an effort in terms of deep leaning algorithm to retrieve an effective text summary for a set of documents. Basically, the proposed system consists of two phases such as training phase and the testing phases. The training phase is used for exploiting the three different algorithms to make the text summarisation process an effective one. Similar to every training phase, the proposed training phases is also possessed of known data and attributes. After that, the testing phase is implemented to test the efficiency of the proposed approach. For experimentation, we used four documents sets which are selected from the DUC (2002). The experimental evaluation showed expected results as, the average precision of 78%, the average recall of 1 and the average f-measure of 84%.