Building hypertext links by computing semantic similarity

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, a vulnerability to the effects of synonymy (many words for the same concept) and polysemy (many concepts for the same word). We propose a novel method for automatic hypertext generation that is based on a technique called lexical chaining, a method for discovering sequences of related words in a text. This method uses a move general notion of document relatedness, and attempts to take into account the effects of synonymy and polysemy. We 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.