A method of sense resolution is proposed that is based on WordNet, an on-line lexical database that incorporates semantic relations (synonymy, antonymy, hyponymy, meronymy, causal and troponymic entailment) as labeled pointers between word senses. With WordNet, it is easy to retrieve sets of semantically rehted words, a facility that will be used for sense resolution during text processing, as ...

An unsupervised method for word sense disambiguation using a bilingual comparable corpus was developed. First, it extracts statistically significant pairs of related words from the corpus of each language. Then, aligning pairs of related words translingually, it calculates the correlation between the senses of a first-language polysemous word and the words related to the polysemous word, which ...

The most effective paradigm for word sense disambiguation, supervised learning, seems to be stuck because of the knowledge acquisition bottleneck. In this paper we take an in-depth study of the performance of decision lists on two publicly available corpora and an additional corpus automatically acquired from the Web, using the fine-grained highly polysemous senses in WordNet. Decision lists ar...

In the current study, we used eye tracking to investigate whether senses of polysemous words and meanings of homonymous words are represented and processed similarly or differently in Chinese reading. Readers read sentences containing target words which was either homonymous words or polysemous words. The contexts of text preceding the target words were manipulated to bias the participants towa...

In this article, we present an experiment of linguistic parameter tuning in the representation of the semantic space of polysemous words. We evaluate quantitatively the influence of some basic linguistic knowledge (lemmas, multi-word expressions, grammatical tags and syntactic relations) on the performances of a similarity-based Word-Sense disambiguation method. The question we try to answer, b...

Computational semantics and logic-based controlled natural languages (CNL) do not address systematically the word sense disambiguation problem of content words, i.e., they tend to interpret only some functional words that are crucial for construction of discourse representation structures. We show that micro-ontologies and multi-word units allow integration of the rich and polysemous multi-doma...

As we store and distribute a large amount of computerized text, we have an important issue about how we extract useful data effectively from the text data. For this reason, the techniques for classifying text automatically with computers have attached attention. Generally, in a field of text classification, we use a model called Vector Space Model(VSM), in which we map a document into a point i...

Unlike homophonous meanings, which are semantically unrelated (e.g., the use of bat to refer to a baseball bat and a flying rodent), polysemous meanings are systematically related to one another (e.g., the use of book, CD, and video to refer to physical objects, as in 'the leather book', or to the intellectual content they contain, as in 'the profound book'). But do perceived relations among po...