Distributional Semantic

Distributional semantics investigates word meaning by analyzing how words co-occur in text, representing meaning as vectors in a high-dimensional space. Current research focuses on refining these models, addressing challenges like polysemy (multiple word meanings) and the instability of meaning across different corpora, often employing techniques like Word2Vec and exploring the integration of visual information to better align with human semantic understanding. This approach has significant implications for natural language processing tasks, improving semantic analysis and potentially offering deeper insights into the cognitive processes underlying human language comprehension.