Recommender system or Recommendation systems are a subset of information filtering system that used to anticipate the ?evaluation? or ?Preference? that user would feed to an item.Nowadays using recommender systems is so widespread that we can say their usage is one of the most vital necessities of h
Restaurant Recommender System based on Collaborative Filtering for Hyderabad residents
Recommender system or Recommendation systems are a subset of information filtering system that used to anticipate the ‘evaluation’ or ‘Preference’ that user would feed to an item.Nowadays using recommender systems is so widespread that we can say their usage is one of the most vital necessities of human being. These systems have been made to help the users to choose the best alternative on the basis of their preferences. recommender systems were designed to generate suggestions such as items or services based on user interests. The major aim of this project will be to develop a restaurant recommender system based on Collaborative Filtering which will predict a user’s interest in opting restaurants on the basis of the scores generated and the correlation calculated between the users.This is unlike simple rating prediction based recommender system
The major aim of this project will be to develop a restaurant recommender system based on Collaborative Filtering which will predict a user's interest in opting restaurants on the basis of the scores generated and the correlation calculated between the users.
Tentative algorithms: Clustering algorithm (K-means) and collaborative filtering algorithm.
Can change the methods.. according to data collection.
Nowadays using recommender systems is so widespread that we can say their usage is one of the most vital necessities of human being. This system has been made to help the users to choose the best restaurant on the basis of their preferences.
Final project will be in the form of Android App and in Web app.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| API | Miscellaneous | 2 | 1000 | 2000 |
| Total in (Rs) | 2000 |
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