A Location Recommendation Based On User Reviews Using Cart

Janani, V.; Balasubramanian, Lubin; Sasikala, G.; Vidhya, G.; Kowsalya, T.

doi:10.1109/icscan.2019.8878812

Cited by 2 publications

(1 citation statement)

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“…Content-based filtering assumes that user's interest can be represented by looking at the content of items they have shown interests, and items whose content descriptions are similar to the target user's favourite items can be recommended. [4] Recent rating approaches allow users to specify their review in a higher dimension by providing more fields, which provides a 0-5 star rating input for service ,location and sleep quality and displays it to the user as extra information but does not use this rating for finding recommendations [5].…”

Section: Related Workmentioning

confidence: 99%

Hotel Recommendation System Using Hybrid Technique

Gaurav

2020

ijarcs

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Recommendation systems are software techniques used for suggesting items in an automated fashion to users tailored their preferences. Collaborative filtering may be a set of technologies that predict which items during a set of information a specific customer will like supported the preferences of many people. The multi-user based CF will tend to provide accurate recommendations by considering the user preferences in multiple forms and several methods have been proposed and implemented for improving the accuracy of these systems. However, the problem of multi-user recommendations is still considered an optimization problem with single-user and overall rating . In addition, increasing the accuracy in predicting the appropriate items suggested to the user's preferences is one of the main challenges faced in these systems.

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Section: Related Workmentioning

confidence: 99%