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Showing papers presented at "RIAO Conference in 2004"


Proceedings Article
26 Apr 2004
TL;DR: This paper deals with indexation of multi-modal geographic documents by the mean of two constructs: geographic entities, and their semantic relations, and the model induced by these constructs offers semantic indexing and querying possibilities.
Abstract: This paper deals with indexation of multi-modal geographic documents by the mean of two constructs: geographic entities, and their semantic relations. These relations concern more specifically contrast or similarity between the entities with regard to the described phenomenon. Geographic entities are retrieved in both text and maps using proper analysis techniques. Contrast or similarity relations -- identified as discursive structures in the text and as semiologic facts in the map -- are then characterised by dedicated modules. The model induced by these constructs offers semantic indexing and querying possibilities. It also provides a valuable basis for collaborative interpretation of individual components of the multi-modal document. The whole system is deployed in a distributed environment, made interoperable by use of major web standards.

15 citations


Proceedings Article
26 Apr 2004
TL;DR: This article discusses a technique of generating hierarchical topic trees of a text and to use them in various ways to build summaries of a flexible length and compares the results when the topic tree is used for automatic summarization.
Abstract: Summarizing document texts at various levels of detail is required for many information selection tasks For instance, when loading and visualizing documents on small screens of handheld devices, it is important to be able to dynamically compress texts In this article we discuss a technique of generating hierarchical topic trees of a text and to use them in various ways to build summaries of a flexible length For the topic tree building process we have implemented both a deterministic and probabilistic approach We compare the results when the topic tree is used for automatic summarization

2 citations