• Abhijit Gore
• Soham Chavan
• Pratik Nemane
• Utkarsh Kharat
• Prof. Dipa Deshmukh

Traveler reviews are a source of information for tourists to know about tourist attractions. Unfortunately, some reviews are irrelevant and become noisy. The method of classifying sentiment based on views has shown promise in silence. However, very little research has been done on automatic characterization and infrequently identified implications, and co-dependency results in classification. This article presents a framework aspect of the classification of confidence that will not only But identifies very effective aspects But can perform classification tasks with high accuracy The framework has been adopted as a mobile app that helps tourists find the best restaurants or hotels in town. Experimental results show reviews and opinions with precisely extracted aspects and opinion words using our approach to outperform several other well-established methods in identifying opinion features.

Intelligent Tourist Guide Using Django

"Intelligent Tourist Guide Using Django", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.g456-g463, April-2022, Available :http://www.jetir.org/papers/JETIR2204670.pdf

"Intelligent Tourist Guide Using Django", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppg456-g463, April-2022, Available at : http://www.jetir.org/papers/JETIR2204670.pdf