Five different proposed measures of similarity or semantic distance in WordNet were experimentally compared by examining their performance in a real-word spelling correction system. It was found that Jiang and Conrath 's measure gave the best results overall. That of Hirst and St-Onge seriously over-related, that of Resnik seriously under-related, and those of Lin and of Leacock and Chodorow fell in between.

this paper, we examine the idea of lexical chains as such a representation. We show how they can be constructed by means of WordNet, and how they can be applied in one particular linguistic task: the detection and correction of malapropisms.

The quantification of lexical semantic relatedness has many applications in NLP, and many different measures have been proposed. We evaluate five of these measures, all of which use WordNet as their central resource, by comparing their performance in detecting and correcting real-word spelling errors. An information-content–based measure proposed by Jiang and Conrath is found superior to those proposed by Hirst and St-Onge, Leacock and Chodorow, Lin, and Resnik. In addition, we explain why distributional similarity is not an adequate proxy for lexical semantic relatedness. 1.

Spelling errors that happen to result in a real word in the lexicon cannot be detected by a conventional spelling checker. We present a method for detecting and correcting many such errors by identifying tokens that are semantically unrelated to their context and are spelling variations of words that would be related to the context. Relatedness to context is determined by a measure of semantic distance initially proposed by Jiang and Conrath (1997). We tested the method on an artificial corpus of errors; it achieved recall of up to 50% and precision of 18 to 25% -- levels that approach practical usability.

this paper we review models of lexical access in speech production in bilingual speakers. We focus on two major aspects of lexical access: a) how lexical selection is achieved, and b) whether lexical access involves cascaded or discrete stages of processing. We start by considering the major assumptions of how lexical access works in monolingual speakers, and then proceed to discuss those assumptions in the context of bilingual speakers

this paper, we examine the idea of lexical chains as such a representation. We show how they can be constructed by means of WordNet, and how they can be applied in one particular linguistic task: the detection and correction of malapropisms