11-09-2014, 02:57 PM
COMPARATIVE LEARNING OF COLLECTIVE BEHAVIOUR USING K-MEANS AND K-MEDIOD ALGORITHMS
COMPARATIVE.pptx (Size: 294 KB / Downloads: 9)
COLLECTIVE BEHAVIOR LEARNING
The study of collective behavior is to understand how individuals behave in a social networking environment.
We aim to learn to predict collective behavior in social media.
ADVANTAGES OF PROPOSED SYSTEM
Analyzes the data to generate analyzed grouping structures facilitating analysis of the network of users created.
This scalable approach offers a viable solution to effective learning of online collective behavior on a large scale.
Social Networking
This will facilitate the user interaction related to social domains and accordingly the system will analyze behaviors of the users .
CONCLUSION
Social Networking is an important aspect of today’s world.
This app helps in predicting the behaviour of an individual while surfing the web.
Helps in connectivity of people with common interests.