COMPARATIVE ANALYSIS OF LINK PREDICATION TECHNIQUES

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dc.contributor.authorHaseeb Ahmad
dc.date.accessioned2025-10-04T06:55:22Z
dc.date.available2025-10-04T06:55:22Z
dc.date.issued2018
dc.description.abstractIn data mining, predication is the most attracting and beneficial in terms of making the right decision. Recently Link predication proofed its importance to the many researches in general and specially in the social network analysis, bio informatics, complex interconnected network, and chemical interconnection network. By finding the missing links many of the complex pattern in the big data had been found that had made the worth of the old data that is present in our archives, by finding the missing links many answer of complex patterns in big data are being answered. Different kind of algorithms had been purposed to find the links from the graph based data which are categories into three main categories maximum likelihood base algorithms, probability base algorithms and similarity base algorithms and each one is best in its own context, as many researchers had done research on link mining or link predication in each one of above mention algorithms category. So in that research I am going to survey purposed algorithms belong to these categories so from their survey result I will do a comparative analysis and will close the survey with the results and discussion and also on survey results will suggest about furthers directions.
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/7904
dc.language.isoen
dc.publisherUMT, Lahore
dc.titleCOMPARATIVE ANALYSIS OF LINK PREDICATION TECHNIQUES
dc.typeThesis
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