Mobile-Based Emergency Response System Using Ontology-Supported Information Extraction
- Publication Type:
- Chapter
- Citation:
- 2012, 33 pp. 429 - 449
- Issue Date:
- 2012-12-01
Closed Access
Filename | Description | Size | |||
---|---|---|---|---|---|
![]() | 2012001653OK.pdf | 452.41 kB |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
This chapter describes an algorithm within a Mobile-based Emergency Response System (MERS) to automatically extract information from Short Message Service (SMS). The algorithm is based on an ontology concept, and a maximum entropy statistical model. Ontology has been used to improve the performance of an information extraction system. A maximum entropy statistical model with various predefined features offers a clean way to estimate the probability of certain token occurring with a certain SMS text. The algorithm has four main functions: to collect unstructured information from an SMS emergency text message; to conduct information extraction and aggregation; to calculate the similarity of SMS text messages; and to generate query and results presentation. © Springer-Verlag Berlin Heidelberg 2012.
Please use this identifier to cite or link to this item: