14,398 research outputs found
ENRICHMENT AND POPULATION OF A GEOSPATIAL ONTOLOGY FOR SEMANTIC INFORMATION EXTRACTION
The massive amount of user-generated content available today presents a new challenge for the geospatial domain and a great opportunity to delve into linguistic, semantic, and cognitive aspects of geographic information. Ontology-based information extraction is a new, prominent field in which a domain ontology guides the extraction process and the identification of pre-defined concepts, properties, and instances from natural language texts. The paper describes an approach for enriching and populating a geospatial ontology using both a top-down and a bottom-up approach in order to enable semantic information extraction. The top-down approach is applied in order to incorporate knowledge from existing ontologies. The bottom-up approach is applied in order to enrich and populate the geospatial ontology with semantic information (concepts, relations, and instances) extracted from domain-specific web content
Neogeography: The Challenge of Channelling Large and Ill-Behaved Data Streams
Neogeography is the combination of user generated data and experiences with mapping technologies. In this article we present a research project to extract valuable structured information with a geographic component from unstructured user generated text in wikis, forums, or SMSes. The extracted information should be integrated together to form a collective knowledge about certain domain. This structured information can be used further to help users from the same domain who want to get information using simple question answering system. The project intends to help workers communities in developing countries to share their knowledge, providing a simple and cheap way to contribute and get benefit using the available communication technology
Geospatial database generation from digital newspapers: use case for risk and disaster domains.
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.The generation of geospatial databases is expensive in terms of time
and money. Many geospatial users still lack spatial data. Geographic
Information Extraction and Retrieval systems can alleviate this problem.
This work proposes a method to populate spatial databases automatically
from the Web. It applies the approach to the risk and disaster domain
taking digital newspapers as a data source. News stories on digital
newspapers contain rich thematic information that can be attached
to places. The use case of automating spatial database generation is
applied to Mexico using placenames. In Mexico, small and medium
disasters occur most years. The facts about these are frequently mentioned
in newspapers but rarely stored as records in national databases.
Therefore, it is difficult to estimate human and material losses of those
events.
This work present two ways to extract information from digital news
using natural languages techniques for distilling the text, and the national
gazetteer codes to achieve placename-attribute disambiguation.
Two outputs are presented; a general one that exposes highly relevant
news, and another that attaches attributes of interest to placenames.
The later achieved a 75% rate of thematic relevance under qualitative
analysis
The DIGMAP geo-temporal web gazetteer service
This paper presents the DIGMAP geo-temporal Web gazetteer service, a system providing access to names of places, historical periods, and associated geo-temporal information. Within the DIGMAP project, this gazetteer serves as the unified repository of geographic and temporal information, assisting in the recognition and disambiguation of geo-temporal expressions over text, as well as in resource searching and indexing. We describe the data integration methodology, the handling of temporal information and some of the applications that use the gazetteer. Initial evaluation results show that the proposed system can adequately support several tasks related to geo-temporal information extraction and retrieval
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A multi-INT semantic reasoning framework for intelligence analysis support
Lockheed Martin Corp. has funded research to generate a framework
and methodology for developing semantic reasoning applications to support the
discipline oflntelligence Analysis. This chapter outlines that framework, discusses
how it may be used to advance the information sharing and integrated analytic
needs of the Intelligence Community, and suggests a system I software
architecture for such applications
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