CONFERENCE / ICCAIS-2026

Research Article

A Semantic and Context-Aware Conversational AI System for Personalized Travel Planning

K.K.V. Naga Jyothi1 Dr. Shaik Mohammad Rafee2 M. Surya Satya Sri3 P. Suvarna Anjali4 D. Ekshitha Vardhini5
1 3 4 5 Department of Artificial Intelligence and Machine Learning, Sasi Institute of Technology and Engineering Tadepalligudem, Andhra Pradesh, India. 2 Head of Department, Department of Artificial Intelligence and Machine Learning, Sasi Institute of Technology and Engineering Tadepalligudem, Andhra Pradesh, India.

Published Online: 2026

Pages: 66-71

Abstract

In this approach, the idea of creating a vector-based DB that combined both LLM’s and semantic searching will be utilized. Besides, user interface interactions and context aware conversational recommendations will also be combined. Users will therefore interact with the chatbot both in text and voice, giving them a more personal feel. Added to this is real-time external API’s that provides additional context to better customize the itineraries generated for the users based on their preferences, which includes destination selection, travel budget sensitivity, style of travel, and group size. Another feature being added to the itinerary being generated is exporting itineraries into PDF formats. The proposed Chatbot presents examples of using the power of Conversational AI, semantic search, multi-modal interfaces, and real-time data integration to enhance personalization and usability in travel planning systems.

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https://indjcst.com/conference/10.59256/indjcst.20260501C011