Observational Study On Algorithms On The Social Networks

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OBSERVATIONAL STUDY ON ALGORITHMS On exploring Link prediction on the social networks, it lead to various studies in terms of its nature and its peculiarities. As we all know that Social Network is dynamic in nature. New links comes into picture and new relations are formed in later times. Based on the approach we assign the weight to each link from the starting node and ending node. Score (A, B) between the node A and B. The ranks between the pairs (A, B) and (X, Y) is the shortest path in G. One most used measure is the common neighbors. The more and more number of surrounding neighbors similar between A and B would determine that would be possible of forming link in future. Fuzzy k closest friend with a number depth. Here for…show more content…
We can find out the vector for each friends, friend. Sample vector from the above calculation would lead to: For X5: Cricket 0.3, Golf 0.2, and Football 0.5 For X4: golf 0.2, football: 0.4, ping pong 0.1 For X3: Ping-Pong 0.3, basketball 0.2, football 0.3, Chess 0.2 Similarly do it for all the friends and get the aggregated results: we get the final vector as Football 0.145, cricket 0.075, Chess 0.023, Ping-Pong 0.059, Golf 0.083, Basketball 0.024 Applying the agglomerative clustering algorithm in this results set would yield the result as “Football”. This proves that the work of the data mining proved effective in determining the link and relations amongst the network. LIMITATION & CHALLENGES & APPLICATIONS IN DATA MINING OF SOCIAL NETWORKS A. Problems Most common problems are: 1) What if the Data is inconsistent? We might have several contradictions in our data 2) What if the Data is incorrect? We know the information is wrong for a particular case 3) Data can also be incomplete. Several parts of information might be missing. 4) Security Issues like personal and financial details are part of the data. 5) Privacy issue which can lead to purchase of item exposes the card details, if it gets hacked. 6) Misuse of information, if it gets into hand of unethical people, making it vulnerable. B. Limitations Here are few limitation that stand as a hurdle in reaching apex of the Data
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