Nowadays, a huge quantity of information is stored in digital format. A great portion of this
information is constituted by textual and unstructured documents, where geographical …

This paper briefly introduces several of the aspects to take into account in order to properly
describe and analyze the expression of uncertainty in textual data. Different types of …

In the context of using semantic resources for information retrieval, the relationship and
distance between concepts are considered important for word sense disambiguation. In this …

Problem statement: The way of referring to a place in the geographical space can be formal,
based on the spatial coordinates, or informal, which we use in natural language by using …

En los ltimos a os, la geograf a ha adquirido una importancia cada vez mayor en el
contexto de la recuperaci n de la informaci n (Information Retrieval, IR) y, en general, del …

A novel unsupervised genetic word sense disambiguation (GWSD) algorithm is proposed in
this paper. The algorithm first uses WordNet to determine all possible senses for a set of …

Ontology Learning is defined as the set of methods used for building from scratch, enriching
or adapting an existing ontology in a semi-automatic fashion using heterogeneous …

In this paper we address the problem of Word Sense Disambiguation by introducing a
knowledge-driven framework for the disambiguation of nouns. The proposal is based on the …

The CIAOSENSO WSD system is based on Conceptual Density, WordNet Domains and
frequences of WordNet senses. This paper describes the upvunige-CIAOSENSO WSD …

Word sense disambiguation (WSD) is the process of assigning a meaning to a word based
on the context in which it occurs. The absence of sense tagged training data is a real …