分析知识网络中的未来节点

2016 IEEE International Congress on Big Data (BigData Congress) Pub Date : 2016-06-01 DOI:10.1109/BigDataCongress.2016.57

Sukhwan Jung, T. Lai, Aviv Segev

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引用次数: 5

摘要

本文提出了利用网络分析进行知识预测的新方法，并引入了pEgonet，即由新知识的邻域组成的知识网络中的子网络。初步结果表明，利用pEgonet的基本特性预测未来知识如何添加到知识网络中是可行的。本文提出了最初的工作，将扩展到推导一种方法来预测标记的未来知识，其影响和结构。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Analyzing Future Nodes in a Knowledge Network

The paper proposes new methods for knowledge prediction using network analytics and introduces pEgonet, sub-networks within knowledge networks consisting of to-beneighbors of new knowledge. Preliminary results show that it is feasible to predict how future knowledge is added in the knowledge network by utilizing basic properties of pEgonet. The paper presents initial work which will be expanded to derive a method to predict labelled future knowledge, with its impact and structures.

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2016 IEEE International Congress on Big Data (BigData Congress)

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