|
Descripción
|
|
|---|---|
| Effective data summarization methods that use AI techniques can help humans understand large sets of data. In this paper, we describe a knowledge-based method for automatically generating summaries of geospatial and temporal data, i.e. data with geographical and temporal references. The method is useful for summarizing data streams, such as GPS traces and traffic information, that are becoming more prevalent with the increasing use of sensors in computing devices. The method presented here is an initial architecture for our ongoing research in this domain. In this paper we describe the data representations we have designed for our method, our implementations of components to perform data abstraction and natural language generation. We also discuss evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions. | |
|
Internacional
|
No |
|
Nombre congreso
|
2009 21st IEEE International Conference on Tools with Artificial Intelligence |
|
Tipo de participación
|
960 |
|
Lugar del congreso
|
Newark, EEUU |
|
Revisores
|
Si |
|
ISBN o ISSN
|
1082-3409 |
|
DOI
|
10.1109 |
|
Fecha inicio congreso
|
02/11/2009 |
|
Fecha fin congreso
|
05/11/2009 |
|
Desde la página
|
485 |
|
Hasta la página
|
492 |
|
Título de las actas
|
Proceedings 2009 21st IEEE International Conference on Tools with Artificial Intelligence |