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Extracting Patterns in Social Network by Means of Link Mining

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dc.contributor.author Oo, Hnin Wut Yee
dc.contributor.author Aung, Than Htike
dc.date.accessioned 2019-07-24T15:43:22Z
dc.date.available 2019-07-24T15:43:22Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1247
dc.description.abstract The World Wide Web serves as a huge, widely distributed, global information service center for news, advertisements, consumer information, financial management, education, government, e-commerce, and many other information services. The Web contains a rich and dynamic collection of hyperlink information which can access usage information and provide rich sources for data mining. It is a highly dynamic information source and web service centers update their web pages regularly. Linkage information and access are also updated frequently. This framework is the distillation of broad search topics, through the discovery of “authoritative” information sources on topics. This using hubs, called HITS (Hyperlink-Induced Topic Search) to find authoritative pages based on the relationship between a set of relevant authoritative pages and the set of “hub pages” that join them together in the link structure. This formulation has connections to the eigenvectors of certain matrices associated with the link graph. This HITS algorithm provides surprisingly good search results for a wide range of query. en_US
dc.language.iso en en_US
dc.publisher Fifth Local Conference on Parallel and Soft Computing en_US
dc.subject Link analysis en_US
dc.subject HITS algorithm en_US
dc.subject Kleinberg algorithm en_US
dc.subject hubs en_US
dc.subject authorities en_US
dc.subject networks en_US
dc.title Extracting Patterns in Social Network by Means of Link Mining en_US
dc.type Article en_US

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