monitoring and clustering events in knowledge engineering
G.Almas Fathima ,K.Bamavathi,P.Kalaiarasi
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:4 Issue:3 Year: 01 April,2016 Pages:752-759
Abstract
Tweet streams provide a variety of real life and real time information on social events that dynamically change over time. In this paper, Although social event detection has been actively studied, how to efficiently monitor evolving events from continuous tweet streams remains open and challenging. However, this approach does not track the evolution of events, nor does it address the issue of efficient monitoring in the presence of a large number of events. In this project, we capture the dynamics of events using four event operations create, absorb, split and merge of tweets, which can be effectively used to monitor evolving events. First the post is created. The post includes images. Then, the post is absorbed and monitored. The post is then splitted to groups and members. Merged when search is done. The posted tweet is grouped by a keyword in that post. Tweet is compared by text summerization and is grouped using the keyword. When a tweet is posted it is compared by another post and forms a group using the words in the tweet and another post comes in it is also compared and grouped. The post doesnt match the title is belong to a member. The results demonstrate the promising performance of our event monitoring and grouping methods on both efficiency and effectiveness
Kewords
event monitoring, merge, automatic group.
Reference
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