Applying Collaborative Filtering Method For Document Recommender System
10 months ago
Authors:
Phan Thị Phương Nam,Lý Quốc Hưng
Publication date:
01 / 06 / 2023
Name of Publishers:
Tra Vinh University Journal of Science
Abstract:
The recommender system helps recommend relevant information items to the user. In recommender systems, collaborative filtering is commonly used to gauge users' interest in new products. Collaborative filtering systems often rely on data about the similarity of users or products in the system in the past to predict preferences or new products for specific users. In this article, we apply the collaborative filtering technique with the k-nearest neighbor to recommend documents for the English center. The implementation process includes the following steps: Firstly, we build a system to collect and store data in the database. In the next step, we implement a recommendation algorithm with three cases: Case 1: For new users; Case 2: For users who have seen the most document items; and Case 3: For centers' members. The results make it easier for users to find documents.