Recent developments in recommender systems: A survey
In this technical survey, the latest advancements in the field of recommender systems are
comprehensively summarized. The objective of this study is to provide an overview of the …
comprehensively summarized. The objective of this study is to provide an overview of the …
Deep learning on knowledge graph for recommender system: A survey
Recent advances in research have demonstrated the effectiveness of knowledge graphs
(KG) in providing valuable external knowledge to improve recommendation systems (RS). A …
(KG) in providing valuable external knowledge to improve recommendation systems (RS). A …
Daisyrec 2.0: Benchmarking recommendation for rigorous evaluation
Recently, one critical issue looms large in the field of recommender systems–there are no
effective benchmarks for rigorous evaluation–which consequently leads to unreproducible …
effective benchmarks for rigorous evaluation–which consequently leads to unreproducible …
CLAVER: An integrated framework of convolutional layer, bidirectional LSTM with attention mechanism based scholarly venue recommendation
Scholarly venue recommendation is an emerging field due to a rapid surge in the number of
scholarly venues concomitant with exponential growth in interdisciplinary research and …
scholarly venues concomitant with exponential growth in interdisciplinary research and …
Cross-domain knowledge graph chiasmal embedding for multi-domain item-item recommendation
Recommender system can provide users with the required information accurately and
efficiently, playing a very important role in improving users' life experience. Although …
efficiently, playing a very important role in improving users' life experience. Although …
Efficient deep reinforcement learning-enabled recommendation
Existing recommendations based on machine learning are mainly based on supervised
learning. However, these methods affected by historical behavior often bring great difficulties …
learning. However, these methods affected by historical behavior often bring great difficulties …
Personalised context-aware re-ranking in recommender system
X Liu, G Wang, MZA Bhuiyan - Connection Science, 2022 - Taylor & Francis
Recommender systems can help correlate information and recommend personalised
services to users as a general information filtering tool. However, contextual factors …
services to users as a general information filtering tool. However, contextual factors …
Hotspot Information Network and Domain Knowledge Graph Aggregation in Heterogeneous Network for Literature Recommendation
W Chen, Y Zhang, Y Xian, Y Wen - Applied Sciences, 2023 - mdpi.com
Tremendous academic articles face serious information overload problems while supporting
literature searches. Finding a research article in a relevant domain that meets researchers' …
literature searches. Finding a research article in a relevant domain that meets researchers' …
Kernel meets recommender systems: A multi-kernel interpolation for matrix completion
A primary research direction for recommender systems is matrix completion, which attempts
to recover the missing values in a user–item rating matrix. There are numerous approaches …
to recover the missing values in a user–item rating matrix. There are numerous approaches …
[HTML][HTML] Recommender system: A comprehensive overview of technical challenges and social implications
The proliferation of Recommender Systems (RecSys), driven by their expanding application
domains, explosive data growth, and exponential advancements in computing capabilities …
domains, explosive data growth, and exponential advancements in computing capabilities …