Domain-Independent Natural Language Processing of text using Unsupervised Translation

  • Adeel Munawar Department of Computer Science, Lahore Garrison University, Lahore, Pakistan
Keywords: Text-to-speech; Natural Language Processing; Artificial Intelligence; Text Meaning Extraction System; grammar pattern; information retrieval; Intelligent Agents

Abstract

NLP is one of the very important domains of artificial intelligence. Nowadays, advancements are being made and NLP is one of the most developing fields. In this paper, we offer a mutual use of unsupervised translation with n-grams and Natural Language Processing techniques to challenge the difficulty of unsupervised translation extraction from textual data. To build a Text Meaning Extraction System, we have to deliver one important element which is input text. This study
presented a different algorithm to work out resemblances between natural languages, by using sequence package analysis and changing them into n-grams. Whenever the sentences that are grammatically difficult and quite lengthy are applied to see the results of the presented algorithm, there are quite efficient results in a semantic reaction. To enhance the experience in the field of AI and search engines, this research paper shows how to improve the handling capability of fuzzy concepts within computers. For example, when search jobs are executed in search engines small textual concepts or sentences might be semantically formed to switch the keyword-based queries. This ability may be functional to intelligent agents to even the procedure of communication between humans and machinery.

Published
2020-09-30
How to Cite
Adeel Munawar. (2020). Domain-Independent Natural Language Processing of text using Unsupervised Translation. Lahore Garrison University Research Journal of Computer Science and Information Technology, 4(3), 71-80. https://doi.org/10.54692/lgurjcsit.2020.0403102
Section
Articles