Aaron Dobrow of the Texas Advanced Computing Center at the University of Texas recently wrote, “Language isn’t always straightforward, even for humans. The multiple definitions in a dictionary can make it difficult even for people to choose the correct meaning of a word. Katrin Erk, a linguistics researcher in the College of Liberal Arts, refers to this as ‘semantic muck.’ Enabled by supercomputers at the Texas Advanced Computing Center, Erk has developed a new method for visualizing the words in a high-dimensional space. Instead of hard-coding human logic or deciphering dictionaries to try to teach computers language, Erk decided to try a different tactic: feed computers a vast body of texts (which are a reflection of human knowledge) and use the implicit connections between the words to create a map of relationships.” Read more