In computational linguistics, word sense disambiguation (WSD) is the problem of determining in which sense a word having a number of distinct senses is used in a given sentence . This paper handles text document clustering as one of the major tasks of text processing. Document clustering is the process of finding out groups of information from the text documents and cluster these documents into...

This paper considers a melody extraction algorithm that estimates the melody in polyphonic audio using the harmonic coded structure (HCS) to model melody in the minimum mean-square-error (MMSE) sense. The HCS is harmonically modulated sinusoids with the amplitudes defined by a set of codewords. The considered algorithm performs melody extraction in two steps: i) pitch-candidate estimation and i...

Word embeddings are high-dimensional vector representations of words and are thus difficult to interpret. In order to deal with this, we introduce an unsupervised parameter free method for creating a hierarchical graphical clustering of the full ensemble of word vectors and show that this structure is a geometrically meaningful representation of the original relations between the words. This ne...

Previous work has shown that adding generalization of the examples in the corpus of an example-based machine translation (EBMT) system can reduce the required amount of pretranslated example text by as much as an order of magnitude for Spanish-English and FrenchEnglish EBMT. Using word clustering to automatically generalize the example corpus can provide the majority of this improvement for Fre...

Sentence clustering plays an important role in theme-based summarization which aims to discover the topical themes defined as the clusters of highly related sentences. However, due to the short length of sentences, the word-vector cosine similarity traditionally used for document clustering is no longer suitable. To alleviate this problem, we regard a word as an independent text object rather t...

This paper investigates the use of clustering techniques in word-sense classification, which identifies different contexts that a word was used with the same or similar sense. For simplicity, we have used the hierarchical clustering techniques: single-and complete-linkage, and we showed that the latter is a more suitable technique from our performance measurements (i. e. recall and precision) c...

Patterns of topological arrangement are widely used for both animal and human brains in the learning process. Nevertheless, automatic learning techniques frequently overlook these patterns. In this paper, we apply a learning technique based on the structural organization of the data in the attribute space to the problem of discriminating the senses of 10 polysemous words. Using two types of cha...