Restaurant Recommendation System (#3572) Browse files * Create README.md * Update README.md * Update README.md * Update README.md * Add files via upload * Create Dataset.md This file contains the google drive link for the dataset. * Create README.md * Add files via upload * Delete...
The Recommendation System Models will be built based on the Yelp Reviews Dataset on Kaggle, particularly focusing on Restaurant Reviews in the city of Toronto. With the models built out, this project can be applied to other cities as long as we can get similar datasets for such cities. Datase...
Then, the system applied the alternative least square technique in matrix factorization and Apache Spark in distributed computing to train the restaurant location dataset. The output was the most relevant restaurant places list to show many choices to users. The ex...
This approach supports semantic operation, which could potentially enables more recommendation scenarios. Our experiments further demonstrated that this approach gained much better performance than classical item representation methods. 展开 被引量: 1 ...
In this work, a real world dataset is considered for the study, where the sales revenue of restaurant is predicted. A second stage regression model built upon base regression models which are linear regression, ridge regression, decision tree regressor. Based on the results obtained, the ...
. Industry reports present additional applications, such as location planning, menu planning, or dynamic preparation times (Oracle2019; Hospitality Tech2018). In the following, only application scenarios for restaurateurs were included and solutions aimed at consumers, e.g. recommendation engines for ...
It also offers the browser-based interface for the users to interact with the system. Using a real restaurant dataset from TripAdvisor, we demonstrate Si~2p can recommend and explore the restaurants in a friendly way.doi:10.14778/3007263.3007296Xiaoye Miao...
The proposed recommendation algorithm is based on contextual post-filtering approach, using the output of a collaborative filtering algorithm together with contextual information of the user's current situation. The dataset used was explicitly acquired through questionnaires answered by 50 users; and the ...
The full dataset of the obtained measures is included inSupplementary Materials Table S1. Conflicts of Interest The authors declare no conflict of interest. Abbreviations The following abbreviations are used in this manuscript: TLVThreshold Limit Values ...