Use of Non-Topological Node Attribute Values for Probabilistic Determination of Link Formation
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2015, Vol 6, Issue 2
Abstract
Here we propose a probabilistic model for determining link formation, using Naïve Bayes Classifier on non-topological attribute values of nodes, in a social network. The proposed model gives a score which helps to determine the relationship strength in a non-formed link. In addition to Naïve Bayes Classifier, weighted Average of the Attribute value match helps to determine the friendship score of a non-formed link. With the increase in online social networks and its influence on people, more and more individuals are getting wider and enhanced social connect. Everyone tries to connect more to explore more. In this race of more, an individual needs better and definitive tools to help them grow their network. Wider is the network more is the possibility to explore. Here we present a novel approach for predicting a link (friendship) between two individuals (nodes) in a social network. The proposed approach uses non-topological attribute data values of both the nodes and predicts linkage possibility by applying Naïve Bayes Classifier on non-topological attribute data values of nodes in existing linkages. A linkage possibility is expressed using one quantitative measure FSCORE. We call it friendship score (FSCORE) between two unconnected individuals. FSCORE is used to predict linkage between two nodes. Higher FSCORE means a higher possibility of linkage between two nodes.
Authors and Affiliations
Abhiram Gandhe, Parag Deshpande
Keywords
Related Articles
- EP ID EP158341
- DOI 10.14569/IJACSA.2015.060227
- Views 136
- Downloads 0
XML Based Representation of DFD
In the world of Information Technology, the working of a information system is well explained with the use of Data Flow Diagrams (DFD). DFDs are one of the three essential perspectives of the Structured Systems Analysis...
A Pheromone Based Model for Ant Based Clustering
Swarm intelligence is a collective effort of simple agents working locally but resulting in wonderful patterns. Labor division, decentralized control, stigmergy and self organization are the major components of swarm int...
Pentaho and Jaspersoft: A Comparative Study of Business Intelligence Open Source Tools Processing Big Data to Evaluate Performances
Regardless of the recent growth in the use of “Big Data” and “Business Intelligence” (BI) tools, little research has been undertaken about the implications involved. Analytical tools affect the development and sustainabi...
Artificial Immune-based Algorithm for Academic Leadership Assessment
Artificial Immune-based algorithm is inspired by the biological immune system as computational intelligence approach in data analysis. Negative selection algorithm is derived from immune-based algorithm’s family that use...
Impact of Heterogeneous Deployment on Source Initiated Reactive Approach
Selection of an optimal number of high energy level nodes and the most appropriate heterogeneity level is a prerequisite in the heterogeneous deployment of wireless sensor network, and it serves several purposes like enh...