Abstract:

Tourist platforms often encounter difficulties in providing personalized location recommendations for tourists. Similarly, tourists also face challenges in choosing locations that align with their interests and preferences. To address these issues, our project seeks to automate the location recommendation process for tourism platforms. By leveraging previous user ratings for public places, we intend to predict suitable locations and offer them to tourism platforms, ultimately improving their performance

Description:

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