ESC: Extractive Summary Construction for Ranking of Customer Criticism using Artificial Neural Networks
C P Sindhu, Ananya Rana, Deepti Bussennagari, Kallepalli Sai Sada Rishi Varma · 2022
In the world we are living today, just knowing the methods of performing a certain task is not important. The procedure is equally necessary to be known and implemented. Conducting research and finding out the best and most efficient algorithm is needed to begin with, but after that implementing that algorithm is also a major part of the research. Summarization and visualization alike, have many different algorithms and libraries that are included for implementation. For summarization, there are certain important steps that are followed. Since, this paper is based on aspect-based summarization, so aspect tagging along with the sentiment classification is done using neural networks techniques. Visualization is a simple but confusing process. It consists of various libraries that are used according to the requirement of the output. The complications in visualizing arise when the dimensions and the basis of pictorial representation have to be identified. In this work, we have used Recurrent Neural Network technique for aspect tagging and Convolutional Neural Network for sentiment classification. This work mainly focuses on summarization of customer reviews of restaurants based on aspects.