https://github.com/tranhungnghiep/AnalyzeKGE
공식 코드Analyzing Knowledge Graph Embedding Methods from a Multi-Embedding Interaction Perspective
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
A knowledge graph is a structured representation of information that organizes data into nodes (entities) and edges (relationships) to show how different pieces of knowledge are interconnected. It enables enhanced data integration, search, and inference by modeling the relationships between concepts and entities in a graph format.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Analyzing Knowledge Graph Embedding Methods from a Multi-Embedding Interaction Perspective
Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding Space
Sora Detector: A Unified Hallucination Detection for Large Text-to-Video Models
On Inductive Abilities of Latent Factor Models for Relational Learning
Generating Explanations to Understand and Repair Embedding-based Entity Alignment
UKP-SQuARE v2: Explainability and Adversarial Attacks for Trustworthy QA
Start Small, Think Big: On Hyperparameter Optimization for Large-Scale Knowledge Graph Embeddings
Friendly Neighbors: Contextualized Sequence-to-Sequence Link Prediction
A Benchmark for Semi-Inductive Link Prediction in Knowledge Graphs
UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction
KGTK: A Toolkit for Large Knowledge Graph Manipulation and Analysis
User-friendly Comparison of Similarity Algorithms on Wikidata
DKEC: Domain Knowledge Enhanced Multi-Label Classification for Diagnosis Prediction
Graph Neural Networks with Learnable Structural and Positional Representations
SpherE: Expressive and Interpretable Knowledge Graph Embedding for Set Retrieval
KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAG
Structure-Augmented Text Representation Learning for Efficient Knowledge Graph Completion
Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering
Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.