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Social Learning Networks: Efficiency Optimization for MOOC Forums

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Presentation on theme: "Social Learning Networks: Efficiency Optimization for MOOC Forums"— Presentation transcript:

1 Social Learning Networks: Efficiency Optimization for MOOC Forums
Christopher G. Brinton, Swapna Buccapatnam, Felix Ming Fai Wong, Mung Chiang, and H. Vincent Poor

2 全文阅读思路 1.做什么? 2.怎么做? 3.难点是什么?

3 1.做什么? 什么叫效率优化? Social Learning Networks:
Efficiency Optimization for MOOC Forums

4 1.做什么?——SLN评价指标 效用F是如何定义的?

5 1.做什么?——效用定义

6 1.做什么?——效用定义的解释 F :目标 U :用户 k :主题 b :收益 e :赤字 s :问题 d :回答

7 1.做什么?——一句话总结 本文主要的工作,就是(1)计算出当前SLN的S、D、W、E,并根据这些值求出当前SLN的F,以及(2)在该网络的S、D下可能求出F最大时W的情况。并通过(3)比较两者得出一些结论。

8 1.做什么?——计算路线图 W、S、D → E W、S、D、E → F

9 2.怎么做? 1.求W 2.求S和D 3.求W* 4.比较,得出结论

10 2.怎么做?——求W

11 2.怎么做?——求S和D

12 2.怎么做?——求W*

13 2.怎么做?——比较,得出结论 1. the observed SLNs have low efficiencies.

14 2.怎么做?——比较,得出结论 2.the observed SLNs are less efficient with respect to a higher importance placed on teaching benefit.

15 2.怎么做?——比较,得出结论 3.SLNs where users respond impartially across neighbors tend to be more efficient. (Given that larger in (6) has the effect of making the weights wu,v more uniform across v)

16 2.怎么做?——比较,得出结论 高效SLN的特征
1. optimization tends to make the degrees more uniform.

17 2.怎么做?——比较,得出结论 高效SLN的特征
2.optimization causes the edge weights to become more homogeneous.

18 2.怎么做?——比较,得出结论 高效SLN的特征
3.optimization also preserves fairness in the distribution of local utilities.

19 2.怎么做?——比较,得出结论 高效SLN的特征
4.optimization improves local utility for the majority of users.

20 难点是什么? 1.根据实际问题建立模型 2.求W*时计算大量数据使用梯度下降法

21 本文的不足 1.没有使用论坛本身的逻辑关系 2.得出结论参考系不合理,结论的说服力不足

22 谢谢 Thank You!


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