Utilizing Deep Learning Techniques for Text and Image Capturing Summarization in Information Retrievals

Abstract

In this paper, a novel information retrieval and text summarization model based on deep learning (DL) is introduced. The model comprises three primary stages, including information retrieval, template generation, and text summarization. The initial step involves utilizing a bidirectional long short term memory (BiLSTM) technique to retrieve textual data. This approach considers each word in a sentence, extracts relevant information, and converts it into a semantic vector.