Emergent System using Tweet Analyzer Naturally Inspired Computing Approach

Nowadays much system has developed to reach the people during disasters. A social interaction with the micro blogging services has vastly increased. Twitter a well popularsocial mediumhas scarcity of attention makes people interacting with each other.Thispaper explores the use of twitter for disaster event using text classifier.It analyses the targeted event with tweeted text and identifies the target and its location. By the use of SVMs, thetext classifiers are achieved.SVM performs the methods of Bayesian filtering for the informative messages of particular event. This methodof filtering works best compare with the other methods for estimating the informative messages. As an application we are sending an E-mail and SMS alert message through the twitter and thedeclared set of friends and followers follows the messages

Supporting flexible, efficient and user-interpretable retrieval of similar time series

Supporting decision making in domains in which the observed phenomenon dynamics have to be dealt with, can greatly benefit of retrieval of past cases, provided that proper representation and retrieval techniques are implemented. In particular, when the parameters of interest take the form of time series, dimensionality reduction and flexible retrieval have to be addresses to this end. Classical methodological solutions proposed to cope with these issues, typically based on mathematical transforms, are characterized by strong limitations, such as a difficult interpretation of retrieval results for end users, reduced flexibility and interactivity, or inefficiency. In this paper, we describe a novel framework, in which time-series features are summarized by means of Temporal Abstractions, and then retrieved resorting to abstraction similarity. Our approach grants for interpretability of the output results, and understandability of the (user-guided) retrieval process. In particular, multilevel abstraction mechanisms and proper indexing techniques are provided, for flexible query issuing, and efficient and interactive query answering. Experimental results have shown the efficiency of our approach in a scalability test, and its superiority with respect to the use of a classical mathematical technique in flexibility, user friendliness, and also quality of results