Flexibly manipulating popularity bias for tackling trade-offs in recommendation
Latent factor models in collaborative filtering (CF) have been the state-of-the-art for over a
decade and widely studied. Most models learn a representation of each user/item and …
decade and widely studied. Most models learn a representation of each user/item and …
Aspect-driven user preference and news representation learning for news recommendation
Intelligent human-device interfaces play key roles in fully automated vehicles (FAVs),
ensuring smooth interactions and improving the driving experience. Listening to news is a …
ensuring smooth interactions and improving the driving experience. Listening to news is a …
BCE4ZSR: Bi-encoder empowered by teacher cross-encoder for zero-shot cold-start news recommendation
MA Rauf, MMY Khalil, W Wang, Q Wang… - Information Processing …, 2024 - Elsevier
In the realm of news recommendations, the persistent challenge of the cold-start problem
continues to impede progress. Existing approaches rely heavily on information exchange …
continues to impede progress. Existing approaches rely heavily on information exchange …
A neural knowledge graph evaluator: Combining structural and semantic evidence of knowledge graphs for predicting supportive knowledge in scientific QA
Effectively detecting supportive knowledge of answers is a fundamental step towards
automated question answering. While pre-trained semantic vectors for texts have enabled …
automated question answering. While pre-trained semantic vectors for texts have enabled …
Content‐based and knowledge graph‐based paper recommendation: Exploring user preferences with the knowledge graphs for scientific paper recommendation
H Tang, B Liu, J Qian - Concurrency and Computation: Practice …, 2021 - Wiley Online Library
Researchers usually face difficulties in finding scientific papers relevant to their research
interests due to increasing growth. Recommender systems emerge as a leading solution to …
interests due to increasing growth. Recommender systems emerge as a leading solution to …
Dual-view hypergraph attention network for news recommendation
News Recommendation (NR) helps users to quickly find their mostly interested information.
Recently, some NR systems based on graph neural networks has achieved significant …
Recently, some NR systems based on graph neural networks has achieved significant …
Package recommendation with intra-and inter-package attention networks
With the booming of online social networks in the mobile internet, an emerging
recommendation scenario has played a vital role in information acquisition for user, where …
recommendation scenario has played a vital role in information acquisition for user, where …
Intention-aware user modeling for personalized news recommendation
Although tremendous efforts have been made in the field of personalized news
recommendations, how to accurately model users' reading preferences to recommend …
recommendations, how to accurately model users' reading preferences to recommend …
Survey on heterogeneous information networks analysis and applications
石川， 王睿嘉， 王啸 - Journal of Software, 2021 - jos.org.cn
实际系统往往由大量类型各异, 彼此交互的组件构成. 目前, 大多数工作将这些交互系统建模为同
质信息网络, 并未考虑不同类型对象的复杂异质交互关系, 因而造成大量信息损失. 近年来 …
质信息网络, 并未考虑不同类型对象的复杂异质交互关系, 因而造成大量信息损失. 近年来 …
基于图卷积的双通道协同过滤推荐算法.
付峻宇， 朱小栋， 陈晨 - Application Research of Computers …, 2023 - search.ebscohost.com
在推荐系统中, 利用图卷积网络等方法提取图的高阶信息缓解了冷启动问题.
为了在此基础上融合神经网络协同过滤的深层特征提取能力, 提出一种基于图卷积的双通道协同 …
为了在此基础上融合神经网络协同过滤的深层特征提取能力, 提出一种基于图卷积的双通道协同 …