Disaster Management Using Ontology Feature

The digital transformation has witnessed an exponential growth in the recent years.This transformation has touched every instance of human life.The current generation rigorously rely in the platform of information storage & retrieval.This originates an ample opportunity for designing and developing systems for societal benefits.The importance of social networking forums has a vital role in our life.The usage of the above websites is frequent towards maintaining identity, keeping connect with the friends, updating personal & professional information, etc.They have increasingly infused itself into daily life.In recent years, one of the important areas of research is oriented towards from the social networking websites in different categories.This paper represents the work done with an open research dataset known as Microblog Track provided by Forum of Information Retrieval & Evaluation (FIRE).The task provided by the FORUM is to develop a suitable model for the identification of tweets.The training dataset consists of two predefined labels, known as need and availability.In this paper, the prediction rate has been optimized by using the term weighting models before applying the classifiers.The experiments showed that the classification accuracy is increased when the term weight is modified by using the information gain method and using the SVM classifier.This system automatically annotated the FIRE-2015 dataset of microblog track with 97% accuracy.