International audienceKnowledge discovery from texts, particularly the identification of spatial information is a difficult task due to the complexity of texts written in natural language. Here we propose a method combining two statistical approaches (lexical and contextual analysis) and a text mining approach to automatically identify types of spatial relations. Experiments conducted on an English corpus are presented
Abstract. Computational approaches in spatial language understanding distinguish and use dierent asp...
In the past few years, texts have become an important spatial data resource, in addition to maps, sa...
Spatial Data Mining is discovering of interesting, implicit knowledge in spatial databases, an impor...
Knowledge discovery from texts, particularly the identification of spatial information is a difficul...
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-SISOInternational audienceKno...
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-SISOInternational audienceKno...
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-SISOInternational audienceKno...
Textual data is available to an increasing extent through different media (social networks, companie...
Textual data is available to an increasing extent through different media (social networks, companie...
Textual data is available to an increasing extent through different media (social networks, companie...
Computational approaches in spatial language understanding nowadays distinguish and use different as...
An increasing amount of textual data is made avail-able through different medium (e.g., social netwo...
This paper is involved with extracting spatial information from text. We seek to geo-reference all s...
[[abstract]]In this paper, we describe a location based text mining approach to classify texts into ...
The extraction of spatial information from textual data has become an important research topic in th...
Abstract. Computational approaches in spatial language understanding distinguish and use dierent asp...
In the past few years, texts have become an important spatial data resource, in addition to maps, sa...
Spatial Data Mining is discovering of interesting, implicit knowledge in spatial databases, an impor...
Knowledge discovery from texts, particularly the identification of spatial information is a difficul...
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-SISOInternational audienceKno...
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-SISOInternational audienceKno...
[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-SISOInternational audienceKno...
Textual data is available to an increasing extent through different media (social networks, companie...
Textual data is available to an increasing extent through different media (social networks, companie...
Textual data is available to an increasing extent through different media (social networks, companie...
Computational approaches in spatial language understanding nowadays distinguish and use different as...
An increasing amount of textual data is made avail-able through different medium (e.g., social netwo...
This paper is involved with extracting spatial information from text. We seek to geo-reference all s...
[[abstract]]In this paper, we describe a location based text mining approach to classify texts into ...
The extraction of spatial information from textual data has become an important research topic in th...
Abstract. Computational approaches in spatial language understanding distinguish and use dierent asp...
In the past few years, texts have become an important spatial data resource, in addition to maps, sa...
Spatial Data Mining is discovering of interesting, implicit knowledge in spatial databases, an impor...