CF‐SBERTHet: Collaborative and Textual Knowledge Enhanced Semantic Graphs for Sparse Recommendations
ABSTRACT Modern e‐commerce platforms face a critical challenge: delivering accurate recommendations under extreme user–item interaction sparsity, where textual context remains systematically underutilised. Existing collaborative filtering methods degrade sharply in sparse settings, while semantic approaches fail to capture collaborative patterns ...
He Ma +7 more
wiley +1 more source
Correction to "Construction of the Adjusted Scoliosis 3D Finite Element Model and Biomechanical Analysis under Gravity". [PDF]
europepmc +1 more source
Link Prediction in Heterogeneous Information Networks: Improved Hypergraph Convolution with Adaptive Soft Voting. [PDF]
Zhang S +6 more
europepmc +1 more source
The metadata ecosystem and AI: Enabling FAIR and AI‐ready data
Abstract Reproducibility is a foundational tenet of science. As artificial intelligence (AI) becomes increasingly embedded across science, the need to accurately document the provenance, structure, and behavior of training data, models, and workflows grows correspondingly. Metadata, understood as explicit and structured knowledge about data and related
Jane Greenberg +5 more
wiley +1 more source
Molecular graph-based invariant representation learning with environmental inference and subgraph generation for out-of-distribution generalization. [PDF]
Zhu H +8 more
europepmc +1 more source
Abstract The exponential growth of scientific literature—over 2.5 million papers and 3.5 million patents annually—poses critical challenges for knowledge discovery. To address these, we propose SCIMKG (Scientific Knowledge Graph), a framework for constructing scientific knowledge graphs via multi‐source heterogeneous multi‐source.
Erxi Zhu, Yuan Hu
wiley +1 more source
Bridging sponsor-site operations through reciprocal on-site training of CRAs and CRCs: Impact on workflow knowledge and behavior among trial staff. [PDF]
Hosono H +10 more
europepmc +1 more source
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu +10 more
wiley +1 more source
Knowledge-based question answering using graph neural networks and contextual language representations. [PDF]
Samir M, Fathy N, Gad W.
europepmc +1 more source
A goodness‐of‐fit test for regression models with discrete outcomes
Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang +2 more
wiley +1 more source

