arXiv (All)
open access
RecKG: Knowledge Graph for Recommender Systems
Knowledge graphs have proven successful in integrating heterogeneous data across various domains. However, there remains a noticeable dearth of research on their seamless integration among heterogeneous recommender systems, despite knowledge graph-based recommender systems garnering extensive resear
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Do All Nodes Benefit Equally from Knowledge Graphs? Adaptive Node-Aware KG Fusion for Recommendation#973527
- MURAL: Multimodal Uncertainty-aware Recommendation via Adaptive edge Learning#927850
- Broad information diffusion modelling for sharing link click prediction using knowledge graphs#824170
- On Mitigating Data Sparsity in Conversational Recommender Systems#629791
- On Mitigating Data Sparsity in Conversational Recommender Systems#627929
Record · ID 1141399
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive