Evaluating decision analytics from mobile big data using rough set based ant colony

Abstract

The significance of mobile centric data from various sensors, mobile phones and from other corresponding sources has already been identified across different sections of applications from commercial services to decision making applications. However, uncertainty and volume of mobile big data solicits appropriate analytics and decision making ability to be inferred from such data sources. Primarily, the data source and analytics to be chosen from the perspective of adaptive yet intelligent technique. The proposed chapter elaborates such solution while deploying rough set, which is capable of handling imprecise and uncertain contexts of mobile big data. In addition to, ant colony pheromone deposition and evaporation process assists in optimal feature selection mechanism for resolved decisions. The proposed model is supported by case study of hazards event and the information of the event is propagated through mobile data derived from social network. The data is represented as social tweets and posts. It has been analyzed with rough set based ant colony.