Word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowledge source. We describe a system which t)erforms word sense disambiguation on al...
We have developed a word sense disambiguation algorithm, following Cheng and Wilensky (1997), to disambiguate among WordNet synsets. This algorithm is to be used in a cross-langua...
This paper presents an algorithm to integrate different lexical resources, through which we hope to overcome the individual inadequacy of the resources, and thus obtain some enric...
In this paper we describe a method for performing word sense disambiguation (WSD). The method relies on unsupervised learning and exploits functional relations among words as prod...
Word sense disambiguation for unrestricted text is one of the most difficult tasks in the fields of computational linguistics. The crux of the problem is to discover a model that ...
Word Sense Disambiguation (WSD), in the field of Natural Language Processing (NLP), consists in assigning the correct sense (semantics) to a word form (lexeme) by means of the cont...
Davide Buscaldi, Giovanna Guerrini, Marco Mesiti, ...
Previous algorithms to compute lexical chains suffer either from a lack of accuracy in word sense disambiguation (WSD) or from computational inefficiency. In this paper, we presen...
This paper presents a new measure of semantic relatedness between concepts that is based on the number of shared words (overlaps) in their definitions (glosses). This measure is ...
We present some of the technology developed at StreamSage for indexing and retrieving audio/video data. A primary difficulty of this task is precise extraction of the passages rel...
Anthony Davis, Philip Rennert, Robert Rubinoff, Ti...
Many Natural Language Processing (NLP) techniques have been used in Information Retrieval. The results are not encouraging. Simple methods (stopwording, porter-style stemming, etc...