@article {10.3844/jcssp.2019.143.160,
article_type = {journal},
title = {Arabic Online Event-Based System for Monitoring and Extracting Infectious Disease-Related Information},
author = {Alruily, Meshrif},
volume = {15},
number = {1},
year = {2019},
month = {Jan},
pages = {143-160},
doi = {10.3844/jcssp.2019.143.160},
url = {https://thescipub.com/abstract/jcssp.2019.143.160},
abstract = {With the revolution of the internet, online data play a significant role in identifying disease outbreaks. This has led researchers, governments and organizations to pay close attention to such data in order to employ and exploit them in developing event-based systems. This research studies the infectious disease outbreaks domain in the Arabic language. In this paper, the Arabic Surveillance Infectious Disease Outbreak System (ASIDOS), which is able to extract infectious disease-related information from unstructured data published by newswires is developed. For identifying the features extraction and performing the data analysis, the word association methodology was adopted. The proposed system is validated through experiments using a corpus collated from different sources. Precision, recall and F-measure are used to evaluate the performance of the proposed information extraction method. The overall results achieved are: precision 94%, recall 74% and F-measure 83%.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}