We propose OntoGain, a system for unsupervised ontology acquisition from unstructured text which relies on multi-word term extraction. For the acquisition of taxonomic relations, we exploit inherent multi-word terms' lexical information in a comparative implementation of agglomerative hierarchical clustering and formal concept analysis methods. For the detection of non-taxonomic relations, we comparatively investigate in OntoGain an association rules based algorithm and a probabilistic algorithm. The OntoGain system allows for transformation of the derived ontology into standard OWL statements. On-toGain results are compared to both hand-crafted ontologies, as well as to a state-of-the art system, in two different domains: the medical and computer science domains.
The need to collect vast amounts of geospatial data is driven by the emergence of geo-enabled Web applications and the suitability of geospatial data in general to organize information. Given that geospatial data collection and aggregation is a resource intensive task typically left to professionals, we, in this work, advocate the use of information extraction (IE) techniques to derive meaningful geospatial data from plain texts. Initially focusing on travel information, the extracted data can be visualized as routes derived from narratives. As a side effect, the processed text is annotated by this route, which can be seen as an improved geocoding effort. Experimentation shows the adequacy and accuracy of the proposed approach by comparing extracted routes to respective map data.
One cannot deny that space and time are important to us. We perceive our world with respect to where and when we do things. We advocate geoblogging as a tool to capture such experiences by means of collecting and organizing notes, images, and in relation to space and time as well as to link them to other geospatial datasets. This demo showcases a Web application that allows for (i) a simple upload of content, geocoding, and map-based authoring of geoblogs as well (ii) querying and linking other geospatial datasets in relation to the geoblog entry.
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