R.I.P.
π»
Ghosted
Can we leverage rating patterns from traditional users to enhance recommendations for children?
August 24, 2018 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Ion Madrazo Azpiazu, Michael Green, Oghenemaro Anuyah, Maria Soledad Pera
arXiv ID
1808.08274
Category
cs.IR: Information Retrieval
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Recommender algorithms performance is often associated with the availability of sufficient historical rating data. Unfortunately, when it comes to children, this data is seldom available. In this paper, we report on an initial analysis conducted to examine the degree to which data about traditional users, i.e., adults, can be leveraged to enhance the recommendation process for children.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Information Retrieval
π
π
Old Age
Neural Graph Collaborative Filtering
R.I.P.
π»
Ghosted
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
R.I.P.
π»
Ghosted
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
R.I.P.
π
404 Not Found
Graph Neural Networks for Social Recommendation
R.I.P.
π»
Ghosted
Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted