We address in this paper the assisted construction of bilingual thematic comparable corpora by means of co-clustering bilingual documents collected from raw sources such as the Web. The proposed approach is based on a quantitative comparability measure and a co-clustering approach which allow to mix similarity measures existing in each of the two linguistic spaces with a ”thematic” comparabilit...

Deriving a thematically meaningful partition of an unlabeled document corpus is a challenging task. In this context, the use of document representations based on latent thematic generative models can lead to improved clustering. However, determining a priori the optimal document indexing technique is not straighforward, as it depends on the clustering problem faced and the partitioning strategy...

Spatial Data Infrastructures at national or higher levels usually comprise the access to multiple geographic data catalogs. However, with classical search systems, it is difficult to have a clear idea of the information contained in the metadata holdings of these catalogs. This paper describes a set of clustering techniques to create a thematic classification of geographic resource collections ...

This paper presents the evaluation methods and the preliminary results of a combined thematic segmentation of (a) meeting documents and (b)meeting speech transcript. Our approach is based on a clustering method applied on a 2D representation of the thematic alignment, and then the projection of the extracted clusters on each axis, corresponding to meeting documents and the speech transcript. Fi...

Automatic summarization is an active research area in natural language processing. This paper has proposed a special method that produces text summary by detecting thematic areas in Chinese document. The specificity of the method is that the produced summary can both cover many different themes and reduce its redundancy obviously at the same time. In this method, the detection of latent themati...

Thematic organization of text is a natural practice of humans and a crucial task for today’s vast repositories. Clustering automates this by assessing the similarity between texts and organizing them accordingly, grouping like ones together and separating those with different topics. Clusters provide a comprehensive logical structure that facilitates exploration, search and interpretation of cu...

In this paper we formally define the problem of automatic detection of thematic categories in a semantically indexed document, and identify the main obstacles to overcome in this process. Furthermore, we explain how detection of thematic categories can be achieved, with the use of a fuzzy quasi-taxonomic relation. Our approach relies on a fuzzy hierarchical clustering algorithm; this algorithm ...

The application of data mining and machine learning technology and especially machine learning clustering algorithms can aid in the design of thematic maps portraying structural characteristics of geographical distributions. However, a review of the literature indicates that such applications are relatively rare. In order to stimulate greater use of clustering algorithms for thematic map design...