Most current automatic hypertext generation systems rely on term repetition to calculate the relatedness of two documents. There are well-recognized problems with such approaches, most notably, they are vulnerable to the linguistic effects of synonymy (many words for the same concept) and polysemy (many concepts for the same word). I propose a novel method for automatic hypertext generation that is based on a technique called lexical chaining, a method for discovering sets of related words in a text. I will also present the results of an empirical study designed to test this method in the context of a question answering task from a database of newspaper articles.
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