A review of text-based recommendation systems
Many websites over the Internet are producing a variety of textual data; such as news,
research articles, ebooks, personal blogs, and user reviews. In these websites, the textual …
research articles, ebooks, personal blogs, and user reviews. In these websites, the textual …
Graph neural news recommendation with user existing and potential interest modeling
Personalized news recommendations can alleviate the information overload problem. To
enable personalized recommendation, one critical step is to learn a comprehensive user …
enable personalized recommendation, one critical step is to learn a comprehensive user …
Is news recommendation a sequential recommendation task?
News recommendation is often modeled as a sequential recommendation task, assuming
there are rich short-term dependencies over historical clicked news. However, users usually …
there are rich short-term dependencies over historical clicked news. However, users usually …
Understanding and modeling passive-negative feedback for short-video sequential recommendation
Sequential recommendation is one of the most important tasks in recommender systems,
which aims to recommend the next interacted item with historical behaviors as input …
which aims to recommend the next interacted item with historical behaviors as input …
Citation recommendation using semantic representation of cited papers' relations and content
J Zhang, L Zhu - Expert systems with applications, 2022 - Elsevier
Citation recommendation can help researchers quickly find supplementary or alternative
references in massive academic resources. Current research on citation recommendation …
references in massive academic resources. Current research on citation recommendation …
Temporal network embedding framework with causal anonymous walks representations
I Makarov, A Savchenko, A Korovko, L Sherstyuk… - PeerJ Computer …, 2022 - peerj.com
Many tasks in graph machine learning, such as link prediction and node classification, are
typically solved using representation learning. Each node or edge in the network is encoded …
typically solved using representation learning. Each node or edge in the network is encoded …
A survey of personalized news recommendation
X Meng, H Huo, X Zhang, W Wang, J Zhu - Data Science and Engineering, 2023 - Springer
Personalized news recommendation is an important technology to help users obtain news
information they are interested in and alleviate information overload. In recent years, news …
information they are interested in and alleviate information overload. In recent years, news …
Temporal sensitive heterogeneous graph neural network for news recommendation
Z Ji, M Wu, H Yang, JEA Íñigo - Future Generation Computer Systems, 2021 - Elsevier
News recommendation plays an important role in alleviating information overload and
helping users find their interesting news. Most of the existing news recommendation …
helping users find their interesting news. Most of the existing news recommendation …
Towards fair and personalized federated recommendation
Recommender systems have gained immense popularity in recent years for predicting
users' interests by learning embeddings. The majority of existing recommendation …
users' interests by learning embeddings. The majority of existing recommendation …
Group-based personalized news recommendation with long-and short-term fine-grained matching
Personalized news recommendation aims to help users find news content they prefer, which
has attracted increasing attention recently. There are two core issues in news …
has attracted increasing attention recently. There are two core issues in news …