Multi-Relational Latent Semantic Analysis
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Word Sense DisambiguationSimilar Papers 제목 키워드 기반
Neural Latent Relational Analysis to Capture Lexical Semantic Relations in a Vector Space
Capturing the semantic relations of words in a vector space contributes to many natural language processing tasks. One promising approach exploits lexico-syntactic patterns as features of word pairs. In this paper, we pr…
Measuring Semantic Similarity by Latent Relational Analysis
This paper introduces Latent Relational Analysis (LRA), a method for measuring semantic similarity. LRA measures similarity in the semantic relations between two pairs of words. When two pairs have a high degree of relat…
Multiple-choiceSemantic SimilaritySemantic Textual SimilarityMulti-Relational Hyperbolic Word Embeddings from Natural Language Definitions
Natural language definitions possess a recursive, self-explanatory semantic structure that can support representation learning methods able to preserve explicit conceptual relations and constraints in the latent space. T…
Learning Word EmbeddingsRepresentation LearningWord Embeddingsr-GAT: Relational Graph Attention Network for Multi-Relational Graphs
Graph Attention Network (GAT) focuses on modelling simple undirected and single relational graph data only. This limits its ability to deal with more general and complex multi-relational graphs that contain entities with…
Graph AttentionKnowledge GraphsLink PredictionA latent factor model for highly multi-relational data
Many data such as social networks, movie preferences or knowledge bases are multi-relational, in that they describe multiple relationships between entities. While there is a large body of work focused on modeling these d…