| Online Social Networks (OSNs) have gained unprecedented popularity in recent years, have grown into an important research area of educational and commercial world. This article chooses the algorithm based on the content similarity to extract OSN from SNS as the object of study, is the effective supplement which studies in the OSN extracting aspect.In the first chapter, there is the research background, goal, significance and research mentality of this paper; In the second chapter, there is the present of the related domain's research present and obtains the rationality which this article studies; In the third, fourth, fifth chapter ,we discuss three aspect which involves to the OSN extraction;In the third chapter, discussing network crawl : get an improved the Best-First crawling algorithm through analyzing the Breadth-first,Depth first,Best-Fist and the characters of the study object , carry on the programming, obtain 5190 Web documents; In the fourth chapter ,we discuss the fuzzy mining algorithms, improved the multi-layer vector space model , on the basis of Analyzing the FCM and FCC methods, improve the text clustering method, Using the F statistics in the procedure of text cluster to obtains the best clustering result;In the fifth chapter, state the society network analysis technology, elaborate the social network's characteristic, and apply the society network analysis technology in the online social network fuzzy excavation model, confirms the excavation result the validity, simultaneously decided whether the model does need to return to the establishment space model vector stage; In the sixth chapter, there is the existing research work summarizes and had pointed out next step studied direction. |
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