One of themain challenges in artificial intelligence or computational linguistics is understanding the meaning of a word or concept.\nWe argue that the connotation of the termââ?¬Å?understanding,ââ?¬Â or the meaning of the word ââ?¬Å?meaning,ââ?¬Â ismerely a wordmapping game\ndue to unavoidable circular definitions. These circular definitions arise when an individual defines a concept, the concepts in its\ndefinition, and so on, eventually forming a personalized network of concepts, which we call an iWordNet. Such an iWordNet serves\nas an external representation of an individualââ?¬â?¢s knowledge and state of mind at the time of the network construction. As a result,\nââ?¬Å?understandingââ?¬Â and knowledge can be regarded as a calculable statistical property of iWordNet topology. We will discuss the\nconstruction and analysis of the iWordNet, as well as the proposed ââ?¬Å?Path of Understandingââ?¬Â in an iWordNet that characterizes an\nindividualââ?¬â?¢s understanding of a complex concept such as a written passage. In our pilot study of 20 subjects we used a regression\nmodel to demonstrate that the topological properties of an individualââ?¬â?¢s iWordNet are related to his IQ score, a relationship that\nsuggests iWordNets as a potential new methodology to studying cognitive science and artificial intelligence.
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