Towards Understanding of Natural Language: Neurocognitive Inspirations

摘要

Neurocognitive processes responsible for representation of meaning and understanding of words are investigated. First a review of current knowledge about word representation, recent experiments linking it to associative memory and to right hemisphere synchronous activity is presented. Various conjectures on how meaning arises and how reasoning and problem solving is done are presented. These inspirations are used to make systematic approximation to spreading activation in semantic memory networks. Using hierarchical ontologies representations of short texts are enhanced and it is shown that high-dimensional vector models may be treated as a snapshot approximation of the neural activity. Clustering short medical texts into different categories is greatly enhanced by this process, thus facilitating understanding of the text.