Generating text descriptions for geographically distributed sensors

Molina, Martin and Sanchez-Soriano, Javier (2011). Generating text descriptions for geographically distributed sensors. In: "IADIS international conference - applied computing 2011", 6-8 Noviembre 2011, Rio de Janeiro, Brazil. ISBN 978-989-8533-06-7.


Title: Generating text descriptions for geographically distributed sensors
  • Molina, Martin
  • Sanchez-Soriano, Javier
Item Type: Presentation at Congress or Conference (Article)
Event Title: IADIS international conference - applied computing 2011
Event Dates: 6-8 Noviembre 2011
Event Location: Rio de Janeiro, Brazil
Title of Book: Proceedings Of The Iadis International Conference Applied Computing 2011
Date: 6 November 2011
ISBN: 978-989-8533-06-7
Freetext Keywords: Multimedia presentation system, natural language generation, geographic information, sensor network
Faculty: Facultad de Informática (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - Non commercial

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Sensor networks, with thousands of geographically distributed sensors and different types of quantitative measures, need software tools to help users understand the meaning of measures. In this paper we pay attention to the problem of automatic generation of geographic descriptions in natural language for geographically distributed sensors. We describe this problem in the context of a web application in the domain of hydrology which is part of a more complex multimedia presentation system that combines text and graphics. We describe the web application and the algorithm that we designed to generate the geographic descriptions for sensors. Besides GIS data files, our method uses two information sources: an online server for geographic names (Geonames) and a specific knowledge base with text patterns that we constructed to process sensor identifiers. The evaluation results confirm that online geographic information resources such as Geonames are useful to generate names for sensors but they need to be combined with other more specific information sources (such as our knowledge base) to obtain good descriptions. We also compare our method with related work and show future lines of work.

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Item ID: 9654
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OAI Identifier:
Deposited by: Javier Sánchez Soriano
Deposited on: 14 Nov 2011 13:24
Last Modified: 06 Mar 2023 09:22
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