Effective Utilization of Shared Nearest Node for Message Diffusion in Social Network Using Dbscan
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2018-12-09 https://doi.org/10.14419/ijet.v7i4.36.24535 -
Shared Nearest Neighbor Clustering (SNN), information diffusion, overlapping nodes, density based clustering, Social Network Analysis (SNA), compels networks, community structure. -
Abstract
The social networking service has been enormously used among various people to share information or to build social relationship between acquaintances and other people as well. This term is used to describe a social structure where many users can bring forth their perspective on certain global information or imbalances that has been occurred over centuries. The goal of Information diffusion is to spread messages over a network with a lesser time complexity and efficient accessibility. Here, to ease the process of message diffusion in social networking, we are finding overlapping nodes between commonly Shared Nearest nodes and aid in spreading the information more appropriately by reducing the complexity in the existing system and promoting an efficient level of performance. Density-based clustering is a relevant method we have used to trace shared nearest neighbor node. Also, we provide security for the data that is being diffused by implementing the RSA security algorithm and providing the security key along with the information and hence the group of people who are eligible to access the data with the security key can only access the data. Hence the information is being diffused evenly to each part in the cluster with less time complexity and efficiency.
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References
[1] Agrawal R, Gehrke J, Gunopulos D &Raghavan P, Automatic subspace clustering of high dimensional data for data mining applications, Vol.27, No.2, (1998), pp.94-105.
[2] Bakshy E, Rosenn I, Marlow C &Adamic L, “The role of social networks in information diffusionâ€, Proceedings of the 21st international conference on World Wide Web, (2012), pp.519-528.
[3] Ertoz L, Steinbach M & Kumar V, “A new shared nearest neighbor clustering algorithm and its applicationsâ€, Workshop on Clustering High Dimensional Data and its Applications at 2nd SIAM International Conference on Data Mining, (2002), pp.105-115.
[4] Gayathri S, Metilda MM &Babu SS, “A Shared Nearest Neighbour Density based Clustering Approach on a Proclus Method to Cluster High Dimensional Dataâ€, Indian Journal of Science and Technology, Vol.8, No. 22, (2015), pp.1-6.
[5] Ilyas MU &Radha H, “Identifying influential nodes in online social networks using principal component centralityâ€, IEEE International Conference on Communications (ICC), (2011), pp.1-5.
[6] Nagpal PB & Mann PA, “Comparative study of density based clustering algorithmsâ€, International Journal of Computer Applications, Vol.27, No.11, (2011), pp.421-435.
[7] Reid F & Hurley N, “Diffusion in networks with overlapping community structureâ€, IEEE 11th International Conference on Data Mining Workshops, (2011), pp.969-978.
[8] Yadav PS, Sharma P & Yadav DK, “Implementation of RSA algorithm using Elliptic curve algorithm for security and performance enhancementâ€, International Journal of Scientific & Technology Research, Vol.1, No.4, (2012), pp.102-105.
[9] Milgram, S & Fergal R, “The small world problemâ€, Psychology Today, Vol.2, No.1, (1967), pp.60–67.
[10] Watts, D & Strogatz, S, “Collective dynamics of ’small-world’ networksâ€, Nature, Vol.393, No.6684, (1998), pp.440–442.
[11] Akshay S. and Apoorva P, “Bandwidth optimized multicast routing algorithm based on hybrid mesh and tree structure with collision control in MANET using lempel-ziv-oberhumer methodâ€, International Conference on Communication and Signal Processing (ICCSP), (2017), pp.0495-0500.
[12] Malvika DMK, Sandhya S & Akshay S, “Control of the Locomotion of Temperature Sensorâ€, International Journal of Applied Engineering Research, Vol.10, No.6, (2015), pp.14405–14419.
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How to Cite
Apoorva, P., Akshay, S., Priyanka, R., & Nayana, N. (2018). Effective Utilization of Shared Nearest Node for Message Diffusion in Social Network Using Dbscan. International Journal of Engineering & Technology, 7(4.36), 802-805. https://doi.org/10.14419/ijet.v7i4.36.24535Received date: 2018-12-21
Accepted date: 2018-12-21
Published date: 2018-12-09