| dc.description.abstract | In the breaking dawn of Internet, the information increase with rapid speed leads to the digital information become overwhelming. Therefore, the Internet users always waste time searching necessary information and they were tired of making decisions every day. Although there are many information retrieval systems such Google search, Bing search, Devil Finder have solved this problem but prioritization and personalization information ware missed. Besides, the enterprises want to take customer’s attention from their websites to increase their revenues. For clarify, the enterprises require that the website must play as a real seller for assisting each customer. It is time for the Recommender System to solve all above problems. By collecting user’s behavior and using the complex algorithms, the Recommender System refine the most appropriate contents for each specific customer.
In light of these facts, the Recommerder System development must be urgently addressed. To contribute for that development, this thesis proposes the framework of the knowledge-based recommendation. Specifically, in Restaurant domain, using ANN models to predict the Service Evaluation and Food Evaluation. | en_US |
