[HTML][HTML] Data science, machine learning and big data in digital journalism: A survey of state-of-the-art, challenges and opportunities
Digital journalism has faced a dramatic change and media companies are challenged to use
data science algorithms to be more competitive in a Big Data era. While this is a relatively …
data science algorithms to be more competitive in a Big Data era. While this is a relatively …
Learning social representations with deep autoencoder for recommender system
With the development of online social media, it attracts increasingly attentions to utilize
social information for recommender systems. Based on the intuition that users are influenced …
social information for recommender systems. Based on the intuition that users are influenced …
Learning adaptive trust strength with user roles of truster and trustee for trust-aware recommender systems
There are two key characteristics of users in trust relationships that have been well
studied:(1) users trust their friends with different trust strengths and (2) users play multiple …
studied:(1) users trust their friends with different trust strengths and (2) users play multiple …
Semantic manifold modularization-based ranking for image recommendation
As the Internet confronts the multimedia explosion, it becomes urgent to investigate
personalized recommendation for alleviating information overload and improving users' …
personalized recommendation for alleviating information overload and improving users' …
Latent semantic indexing-based hybrid collaborative filtering for recommender systems
F Horasan - Arabian Journal for Science and Engineering, 2022 - Springer
Advances in information technologies increase the number and diversity of digital objects.
This increase poses significant problems in reaching the target audience of digital products …
This increase poses significant problems in reaching the target audience of digital products …
Hybrid microblog recommendation with heterogeneous features using deep neural network
J Gao, C Zhang, Y Xu, M Luo, Z Niu - Expert Systems with Applications, 2021 - Elsevier
With the development of mobile Internet, microblog has become one of the most popular
social platforms. The enormous user-generated microblogs have caused the problem of …
social platforms. The enormous user-generated microblogs have caused the problem of …
An effective student grouping and course recommendation strategy based on big data in education
Y Guo, Y Chen, Y Xie, X Ban - Information, 2022 - mdpi.com
Personalized education aims to provide cooperative and exploratory courses for students by
using computer and network technology to construct a more effective cooperative learning …
using computer and network technology to construct a more effective cooperative learning …
The ultimate recommendation system: proposed Pranik System
In today's fast-paced world, recommendation systems have become indispensable tools,
aiding users in making personalized decisions amidst an overwhelming array of choices …
aiding users in making personalized decisions amidst an overwhelming array of choices …
HARSAM: A hybrid model for recommendation supported by self-attention mechanism
D Peng, W Yuan, C Liu - IEEE Access, 2019 - ieeexplore.ieee.org
Collaborative filtering is one of the most commonly used methods in recommendation
systems. However, the sparsity of the rating matrix, cold start-up, and most recommendation …
systems. However, the sparsity of the rating matrix, cold start-up, and most recommendation …
HRS-DC: 基于深度学习的混合推荐模型.
刘振鹏， 尹文召， 王文胜… - Journal of Computer …, 2020 - search.ebscohost.com
针对传统的矩阵分解算法, 仅利用评分信息作为推荐依据, 当评分数据稀疏时,
不能准确获取隐式反馈, 影响推荐的准确性, 充分利用辅助信息进行隐式特征的提取成为研究 …
不能准确获取隐式反馈, 影响推荐的准确性, 充分利用辅助信息进行隐式特征的提取成为研究 …