This paper systematically compares unsupervised word sense discrimination techniques
that cluster instances of a target word that occur in raw text using both vector and similarity …

In this article, we present a novel statistical representation method for knowledge extraction
from a corpus containing short texts. Then we introduce the contrast parameter which could …

This paper presents an unsupervised method for discriminating among the senses of a
given target word based on the context in which it occurs. Instances of a word that occur in …

US researchers said sea shells may be the product of a geological accident that flooded
ancient oceans with calcium, thereby diversifying marine life. Researchers at the US …

Previous partially supervised classification methods can partition unlabeled data into
positive examples and negative examples for a given class by learning from positive labeled …

This paper presents an unsupervised word sense learning algorithm, which induces senses
of target word by grouping its occurrences into a “natural” number of clusters based on the …

We develop a new method for recovering and smoothing fields of surface normals in shape-
from shading. We show how to transform the problem of recovering surface normals that …

In this paper, we propose a word sense learning algorithm which is capable of unsupervised
feature selection and cluster number identification. Feature selection for word sense …

Retrieval systems implementing query-based search routinely encounter difficulties related
to lexical ambiguity. Frequent attempts have been made in the fields of Information Retrieval …

Word sense discrimination is the problem of identifying different contexts that refer to the
same meaning of an ambiguous word. For example, given multiple contexts that include the …