Data Science and Intelligent Computing Techniques
Prediction of Future Word in a Document Using Enhanced LSTM Model
Authors: Naresh Alapati, Suvarchala Linga, Sreelekha Kollipara, Pravallika Gude and Afifa Farheen Shaik
Publishing Date: 16-06-2023
ISBN: 978-81-955020-2-8
Abstract
Prediction of text for Sentence Completion is the often used technology for speeding up communication and reducing overall text writing time. In most cases, when sending messages to individuals, an individual communicates with a certain group of individuals in a particular way. Our goal is to make instant messaging easier for the user by recommending suitable words. The system remembers the previous words encountered in a semantically sound sentence and learns to connect the input word array to its likely the following word. Proposed system can memorize data and handles the information and data for long period of time. It mainly generates results based on the order of input. The system gets trained by the data given by the user and it remembers long sequence of data. The data is then put to use to create a type of software system that is capable of text data modeling, to generate predictions instantaneously.
Keywords
Deep Learning, Next Word Prediction, Long Short-Term Memory.
Cite as
Naresh Alapati, Suvarchala Linga, Sreelekha Kollipara, Pravallika Gude and Afifa Farheen Shaik, "Prediction of Future Word in a Document Using Enhanced LSTM Model", In: Satyasai Jagannath Nanda and Rajendra Prasad Yadav (eds), Data Science and Intelligent Computing Techniques, SCRS, India, 2023, pp. 245-253. https://doi.org/10.56155/978-81-955020-2-8-21