A recommender that gates knowledge-graph injection per node according to measured collaborative-signal stability beats all fourteen comparison methods on three of four benchmarks.
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In: Proceedings of the AAAI Conference on Artifi- cial Intelligence, vol
7 Pith papers cite this work, alongside 3,648 external citations. Polarity classification is still indexing.
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KGEMs for link prediction exhibit high instability in predictions and embeddings from initialization, negative sampling, and other factors, with better MRR not ensuring higher stability.
PARK personalizes academic search by embedding a citation-derived knowledge graph into the same vector space as a neural retrieval model, beating baselines in three of four domains.
Authors release the multimodal WJoconde knowledge graph for French cultural heritage and a LLM-VLM pipeline that extracts and validates new triples from unstructured text and images to extend the graph.
SARMP improves knowledge graph link prediction by selecting the Top-K semantically relevant edges per node and aggregating them with multi-head attention, beating some baselines on FB15k-237 and Kinship but not all benchmarks.
Encoding higher-order structures as heterogeneous property graphs lets standard graph databases support hyperedges, node-tuples, and subgraphs; a Neo4j-based prototype, ACID discussion, complexity analysis, and a GNN accuracy demonstration are presented.
A bidirectional decoder with a graph-aware attention mask, knowledge-masked prediction, and contrastive sub-graph alignment achieves reported state-of-the-art link prediction on Wikidata5M and competitive results on WN18RR.
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Do All Nodes Benefit Equally from Knowledge Graphs? Adaptive Node-Aware KG Fusion for Recommendation
A recommender that gates knowledge-graph injection per node according to measured collaborative-signal stability beats all fourteen comparison methods on three of four benchmarks.
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Link Prediction or Perdition: the Seeds of Instability in Knowledge Graph Embeddings
KGEMs for link prediction exhibit high instability in predictions and embeddings from initialization, negative sampling, and other factors, with better MRR not ensuring higher stability.
-
Multimodal Cultural Heritage Knowledge Graph Extension with Language and Vision Models
Authors release the multimodal WJoconde knowledge graph for French cultural heritage and a LLM-VLM pipeline that extracts and validates new triples from unstructured text and images to extend the graph.