In this article we extend a WordNet structure with relations linking synsets to Desikan’s brain regions. Based on lexicographer files and WordNet Domains the mapping goes from synset semantic categories to behavioural and cognitive functions and then directly to brain lobes. A human brain connectome (HBC) adjacency matrix was utilised to capture transition probabilities between brain regions. We evaluated the new structure in several tasks related to semantic similarity and emotion processing using brain-expanded Princeton WordNet (207k LUs) and Polish WordNet (285k LUs, 30k annotated with valence, arousal and 8 basic emotions). A novel HBC vector representation turned out to be significantly better than proposed baselines.

在本文中，我们扩展了WordNet结构，该结构具有将同义词集链接到Desikan的大脑区域的关系。基于词典词典文件和WordNet域，映射从同义词集语义类别到行为和认知功能，再直接到脑叶。人类大脑连接体（HBC）邻接矩阵用于捕获大脑区域之间的过渡概率。我们使用脑扩展的普林斯顿WordNet（207k LU）和波兰语WordNet（285k LU，30k带有价，唤醒和8种基本情感）评估了与语义相似性和情感处理相关的多项任务中的新结构。事实证明，一种新颖的HBC向量表示形式明显优于建议的基准。