AI Powered Chatbot Using NLP

DOI

10.2991/978-94-6463-858-5_110How to use a DOI?

Keywords

Artificial Intelligence; SentimentAnalysis; Chatbot; Text Processing; Natural Language Processing

Abstract

The increased volume of online messages has made it difficult for users to efficiently process and extract relevant information. This paper presents a flask-based message summary system, allowing users to obtain accurate summary of news articles and simultaneously receive core meaning and context. The system extracts item content from a specific URL, creates extraction summary using latent semantic analysis (LSA), and evaluates the sense of the summarized text using Vader Sentiment analysis. Additionally, the system provides multilingual support using Google Translator and integrates the functionality of the Text-to-Speech for increased accessibility. Readability and understanding based on user settings. The sentiment analysis function categorizes the sound of an article as positive, neutral or negative, and providing users with insight into the emotional tendencies of news content. The GTTS library is used to convert summary into languages. This means systems, text overview techniques, and machine learning to improve news consumption for visually impaired people and users who prefer audio-based news consumption. With this implementation, we want to easily retrieve fast information, minimize read times, and improve user commitment with news content. Based on the ROUGE metrics, the version carried out an normal accuracy of 72.06% indicating a strong perfomance in keeping coherence in the generated summaries.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - A. Shiva Kumar
AU  - Regula Venu
AU  - Kottur Vani
AU  - Akula Pratixith
PY  - 2025
DA  - 2025/11/04
TI  - AI Powered Chatbot Using NLP
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 1320
EP  - 1331
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_110
DO  - 10.2991/978-94-6463-858-5_110
ID  - Kumar2025
ER  -