Please use this identifier to cite or link to this item:
https://dspace.ctu.edu.vn/jspui/handle/123456789/109468
Title: | A PRODUCT REMCOMMENDATION SYSTEM USING BERT4REC MODEL. |
Other Titles: | HỆ THỐNG GỢI Ý SẢN PHẨM SỬ DỤNG MÔ HÌNH BERT4REC |
Authors: | Nguyễn, Thái Nghe Nguyễn, Tú Trinh |
Keywords: | CÔNG NGHỆ THÔNG TIN - CHẤT LƯỢNG CAO |
Issue Date: | 2024 |
Publisher: | Trường Đại Học Cần Thơ |
Abstract: | The rapid growth of data requires systems capable of extracting relevant insights and delivering effective recommendations. Traditional recommendation approaches often face challenges in understanding the relationships and contextual dependencies within large datasets. This creates a need for more robust methods to address these limitations. BERT (Bidirectional Encoder Representations from Transformers) is a language model designed to capture contextual and semantic relationships in text. Its bidirectional processing enables a better understanding of data compared to conventional methods. Integrating BERT into recommendation systems can improve the accuracy and relevance of recommendations by leveraging its capacity for deep context understanding. This study examines the use of BERT in recommendation systems, focusing on its ability to address challenges in traditional approaches. The research evaluates the performance of BERT-based models and their impact on recommendation accuracy and system effectiveness. The findings aim to provide insights into the use of advanced language models for improving recommendation systems. |
Description: | 64 Tr |
URI: | https://dspace.ctu.edu.vn/jspui/handle/123456789/109468 |
Appears in Collections: | Trường Công nghệ Thông tin & Truyền thông |
Files in This Item:
File | Description | Size | Format | |
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_file_ Restricted Access | 2.45 MB | Adobe PDF | ||
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