Word sense disambiguation (WSD) is the ability to identify the meaning of words in context
in a computational manner. WSD is considered an AI-complete problem, that is, a task …

The automatic disambiguation of word senses hasbeen an interest and concern since the
earliest days of computer treatment of language in the 1950s. Sense disambiguation is an" …

We describe a method for the automatic acquisition of the hyponymy lexical relation from
unrestricted text. Two goals motivate the approach:(i) avoidance of the need for pre-encoded …

This paper presents context-group discrimination, a disambiguation algorithm based on
clustering. Senses are interpreted as groups (or clusters) of similar contexts of the …

Researchers in a number of disciplines deal with large text sets requiring both text
management and text analysis. Faced with a large amount of textual data collected in …

5,056,021 10/1991 Ausbom ______ __ 364/419_08 content thereof and may be used for
various purposes such 5,099,426 3/1992 Ca? gren et a1, __ 364/41913 as information …

The WordNet lexical database is now quite large and offers broad coverage of general
lexical relations in English. As is evident in this volume, WordNet has been employed as a …

In this paper, we introduce a WordNetbased measure of semantic relatedness by combining
the structure and content of WordNet with co–occurrence information derived from raw text …

In this paper, we present a new approach for word sense disambiguation (WSD) using an
exemplar-based learning algorithm. This approach integrates a diverse set of knowledge …

This paper presents a method for the resolution of lexical ambiguity of nouns and its
automatic evaluation over the Brown Corpus. The method relies on the use of the wide …