Methods for Automatic Text Generation

Dipti Pawade*, Mansi Jain**, Gauri Sarode***
* Assistant Professor, Department of Information Technology, K.J. Somaiya College of Engineering, Mumbai, India.
**-*** UG Scholar, Department of Information Technology, K.J. Somaiya College of Engineering, Mumbai, India.
Periodicity:December - February'2017
DOI : https://doi.org/10.26634/jcom.4.4.13418

Abstract

In the world of automating tasks and reducing human effort, it is essential for a computer to be able to produce text like humans. This will enable us to let the computer work on insignificant tasks, such as create a summary for an advertisement or a product as well as generate a different outlook on most things like a sequel for a movie or a book. In this paper, the authors aim to review different approaches that have been implemented for generating text based output and devise the most optimal approach that can be used. In this they have compared four different methods used to generate text from various scenarios.

Keywords

Automatic Text Generation, Natural Language Processing, Recurrent Neural Network, Long Short-Term Memory

How to Cite this Article?

Pawade,D., Jain,M., and Sarode,G. (2017). Methods for Automatic Text Generation. i-manager’s Journal on Computer Science, 4(4), 32-36. https://doi.org/10.26634/jcom.4.4.13418

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