Collective Behavior of social Networking Sites
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 2
Abstract
Now a days a huge data is generated by social media like Facebook, Twitter, Flickr, and YouTube This big data present opportunities and challenges to study collective behavior of data. In this work, we predict collective behavior in social media. In particular, given information about some individuals, how can we infer the behavior of unobserved individuals in the same network? A social-dimension-based approach has been shown effective in addressing the heterogeneity of connections presented in social media. However, the networks in social media are normally of colossal size, involving hundreds of thousands of actors. The scale of these networks entails scalable learning of models for collective behavior prediction. To address the scalability issue, we propose an edge-centric clustering scheme to extract sparse social dimensions. With sparse social dimensions, the proposed approach can efficiently handle networks of millions of actors while demonstrating a comparable prediction performance to other non-scalable methods
Authors and Affiliations
Ashwini Vispute, Prerna Jadhav, Prof. P. V Kharat Kharat
Keywords
Related Articles
- EP ID EP147364
- DOI 10.9790/0661-16227579
- Views 84
- Downloads 0
Energetic Hybrid Routing Protocol
Abstract: The networks of sensors are characterized by limited capacity especially at the level of energy saw that the components constitute the network to know the sensors are powered by batteries, which influence on th...
A Survey of Image Segmentation based on Artificial Intelligence and Evolutionary Approach
In image analysis, segmentation is the partitioning of a digital image into multiple regions (sets of pixels), according to some homogeneity criterion. The problem of segmentation is a well-studied one in liter...
An Intelligence System for Detection of Cancer and Diagnosis
Abstract: Currently the digital images are used in various areas like medical, fashion, architecture, face recognition, finger print recognition and bio metrics. Recently the CBIR reduced the semantic gap between t...
A Survey On Data Mining Techniques To Find Out Type Of Heart Attack
Heart disease is a major cause of morbidity and mortality in present society. Medicinal identification is extremely important but complicated task that should be performed precisely and proficiently. Although su...
Computational Analysis of Sequences to Determine Expectation Value Commonly Used in Bioinformatics Database.
Abstract: Solanum lycopersicum economically important crop world wide, intensively investigated and model system for genetic studies in plant ,variability is a measure spread of data set. Genome analysis andannotation us...