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Infectious disease outbreak has a significant impact on morbidity, mortalityand can cause economic instability of many countries. As global trade isgrowing, goods and individuals are expected to travel across the border, aninfected epidemic area carrier can pose a great danger to his hostile. If adisease outbreak is recognized promptly, then commercial products and travelers(traders/visitors) will be effectively vaccinated, and therefore the diseasestopped. Early detection of outbreaks plays an important role here, and bewareof the rapid implementation of control measures by citizens, public healthorganizations, and government. Many indicators have valuable information, suchas online news sources (RSS) and social media sources (Twitter, Facebook) thatcan be used, but are unstructured and bulky, to extract information aboutdisease outbreaks. Few early warning outbreak systems exist with somelimitation of linguistic (Urdu) and covering areas (Pakistan). In Pakistan, fewchannels are published the outbreak news in Urdu or English. The aim is toprocure information from Pakistan's English and Urdu news channels and theninvestigate process, integrate, and visualize the disease epidemic. Urduontology is not existed before to match extracted diseases, so we also buildthat ontology of disease.

BIOPAK Flasher: Epidemic disease monitoring and detection in Pakistan using text mining