双重拒绝与多兴趣融合的对比学习,用于顺序推
Hua Long1, Jianguo Lu2, Chongyang Dai1
1School of Artificial Intelligence, Chongqing University of Technology, Chongqing, 401135, China.
Scientific reports
|December 8, 2025
概括
这项研究引入了D2MFRec,一种新的顺序推方法. 它通过融合多兴趣用户表示和减少行为数据中的噪音来改善预测.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 序列推模型用户行为,以预测未来的互动.
- 多兴趣学习通过捕捉不同的用户偏好来增强建议.
- 现有的方法往往忽略了时间偏好转变和杂的交互数据.
研究的目的:
- 解决顺序推的局限性,特别是忽视时间动态和处理杂数据.
- 提出一种新的双重否定对比学习与多兴趣融合方法 (D2MFRec).
- 在顺序推系统中提高下一个项目预测的准确性和稳定性.
主要方法:
- 开发了一个多兴趣聚合模块,集成单个和多个兴趣表示,用于全面的用户嵌入.
- 引入了双排噪模块,以减轻噪声交互对用户兴趣建模的影响.
- 采用封闭的融合机制,以适应性地将多种兴趣信号组合到统一的用户表示中.
主要成果:
- 与最先进的基线相比,D2MFRec在三个基准数据集中表现优越.
- 拟议的双重拒绝和多利益融合策略显著提高了建议准确性.
- 该方法有效地捕捉了用户时间偏好演变和降低噪音影响.
结论:
- 通过解决时间动态和数据噪声,D2MFRec为顺序建议提供了强大的和有效的解决方案.
- 多兴趣学习与无声化技术的整合在该领域取得了重大进展.
- 这些发现验证了拟议方法在提高下一项预测准确性的有效性.
相关概念视频
Affinity and Avidity
38.4K
Overview
38.4K
Multi-species Conserved Sequences
4.6K
Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...
4.6K
Deconvolution
527
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
527
Multiple Regression
3.7K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.7K
Upsampling
569
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
569
Associative Learning
1.2K
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
Classical conditioning, also known...
1.2K
