https://github.com/CCIIPLab/KGTN
공식 코드Knowledge Enhanced Multi-intent Transformer Network for Recommendation
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.
Knowledge Enhanced Multi-intent Transformer Network for Recommendation
Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset Construction
OKGIT: Open Knowledge Graph Link Prediction with Implicit Types
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks
Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts
Negative Sampling with Adaptive Denoising Mixup for Knowledge Graph Embedding
Neural-Symbolic Models for Logical Queries on Knowledge Graphs
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
Reinforcement Learning based Collective Entity Alignment with Adaptive Features
Towards Entity Alignment in the Open World: An Unsupervised Approach
KGTN-ens: Few-Shot Image Classification with Knowledge Graph Ensembles
PaperRobot: Incremental Draft Generation of Scientific Ideas
Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization
Discovering emergent connections in quantum physics research via dynamic word embeddings
KM-BART: Knowledge Enhanced Multimodal BART for Visual Commonsense Generation
CODER: Knowledge infused cross-lingual medical term embedding for term normalization
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization
Walk Extraction Strategies for Node Embeddings with RDF2Vec in Knowledge Graphs
KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings
Causal Graphs Meet Thoughts: Enhancing Complex Reasoning in Graph-Augmented LLMs
Question-Aware Knowledge Graph Prompting for Enhancing Large Language Models
Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.