EXTRACT ASSOCIATION RULES TO MINIMIZE THE EFFECTS OF DENGUE BY USING A TEXT MINING TECHNIQUE?Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.3, No. 4)
Publication Date: 2014-04-30
Authors : Atif Amin; Ramzan Talib; Salman Raza; Saima Javed;
Page : 394-400
Keywords : Text mining; data mining; association rule mining; Dengue;
Nowadays, dengue (vector-borne tropical viral diseases) has been become the greatest scourge of humankind and there consequence has more impact than any other pathogen in shaping the human genome. Generally in Pakistan specifically in Punjab (Pakistan) Dengue is emerging as one of the major public-health problem. Federal & Provincial Health Governments are taking all possible steps on ―War-Footing‖ to recover such type of diseases. They are determines in making special possibilities to face such type of problems in advance. From WWW, digital libraries, World Health Organization (WHO) and other news sources it is estimated that about 2.5 billion people, or 40 percent of the world’s population, live in areas where there is a risk of dengue transmission because Dengue flourishes in urban poor areas, suburbs and the countryside but also affects more affluent neighborhoods in tropical and subtropical countries. As of November 2011, it has killed over 300 people in the last several months and over 14,000 are infected by this mosquito-borne disease. Majority of the people infected are from the Lahore area in Punjab, Pakistan. As a matter of fact, if a virus attacks on somewhere, what will be its next target in geographically aspects, because dengue virus will be spread from one place to other from contaminated water and mosquito. Therefore by using above said data sources, performing some preprocessing techniques such as transformation, filtration, stemming and indexing of the documents and then applying data mining techniques our system will not only helps to identify geographical spreading patterns of the viruses but it also helps to suggest proactively next geographical location where virus has most probability to attach so that government can take remedy measures.
Other Latest Articles
Last modified: 2014-04-14 18:40:42