Location based personalized recommendation systems for the tourists in India

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Sachi Nandan Mohanty

Kalinga Institute of Industrial Technology, India

: J Comput Eng Inf Technol

Abstract

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In the domain of tourism sector, this study examines the collaborative filtering in recommender system by categorizing users according to their choice of place, food, local item purchase etc. The proposed system will store the opinions of the local users about the spots and the foods and products for purchase available in those spots. It uses collaborative filtering techniques to find the similar users to a given querying user. The system recommends the best spots along with good food and products available in those spots. Two hundred (male: 110, female: 90) married individuals from Bhubaneswar, Odisha (India) participated in the study. Cosine similarity is used in the proposed system to find the similar users of a given input query user. The results revealed that collaborative filtering is the more reliable technique for personalized recommender systems. The performance of the proposed system is evaluated in terms of precision recall and f-measure values.

Biography

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