Visualization of biological patterns in event detection and tracking based on SRP algorithm

The goal of this paper is to provide a temporal visual structure, which helps in easy identification of the amount of information the story adds to the event in an event detection and tracking task. The strength of the event is calculated each time the story arrives and is plotted in a visual structure. The relationship of the story with an event is found applying a biological species interaction approach towards the incoming news stories and events. The biological model proposed in this paper helps in classifying the story type by considering the interaction among the species as relationship with the events. The fitness score of the story to the event is calculated using SRP algorithm. This score together with the relation type helps in calculating the strength of the event, which is used to plot on a temporal visual structure. There is a combined display of archive events with the present stories which gives a clear view of the importance of news in the stories.