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Research Paper | Computer Science and Engineering | Volume 15 Issue 4, April 2026 | Pages: 1867 - 1870 | India
Intelligent Tourism Analytics Platform for Classification, Prediction and Recommendation
Abstract: Tourism platforms generate large volumes of data from user profiles, travel searches, bookings, ratings, reviews, seasonal demand and destination attributes. This paper presents an intelligent tourism analytics platform that integrates classification, prediction and recommendation techniques to support tourists and tourism service providers. The proposed system classifies tourists based on travel purpose and preference category, predicts destination demand and booking probability, and recommends suitable destinations, hotels, activities and travel packages. The methodology uses data preprocessing, feature extraction, machine learning-based classification, regression-based prediction and hybrid recommendation models. The platform improves decision-making by converting raw tourism data into useful insights for personalized travel planning and business optimization. The proposed approach can assist travel agencies, hotel booking systems, smart tourism portals and destination management organizations in improving customer satisfaction, service relevance and operational efficiency.
Keywords: Tourism Analytics, Classification, Prediction, Recommendation System, Machine Learning
How to Cite?: Nandhu Prasad, Rinsa Rees, "Intelligent Tourism Analytics Platform for Classification, Prediction and Recommendation", Volume 15 Issue 4, April 2026, International Journal of Science and Research (IJSR), Pages: 1867-1870, https://www.ijsr.net/getabstract.php?paperid=SR26430082543, DOI: https://dx.dx.doi.org/10.21275/SR26430082543