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# System prepended metadata

title: 12-26 meeting
tags: [meeting]

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tags: meeting
---

# 12-26 meeting
> 奧丁丁期中成果快完成了
## 前情提要
![](https://i.imgur.com/it0el09.jpg)

* Abstract值域: 正負0.001~1
![](https://i.imgur.com/UxrOQo3.png)

* Deepwalk值域: 正負0.0001~0.01
![](https://i.imgur.com/1dCQkGq.png)

<!-- * Embedding Predictions: -->

<!-- ![](https://i.imgur.com/QBYCN5f.png) -->

<!-- * KNN recommend paper id: -->

<!-- ![](https://i.imgur.com/NVlXIkD.png) -->

* 用Deepwalk做實驗:
    ![](https://i.imgur.com/GXwE4u9.png)

    * 五層relu + linear, 加上BatchNormalize, batch_size=128
    ![](https://i.imgur.com/6NGURnq.png)

    * 五層sigmoid + linear, 加上BatchNormalize, batch_size=128
    ![](https://i.imgur.com/DRjBCfV.png)

    * 五層tanh + linear, 加上BatchNormalize, batch_size=128
    ![](https://i.imgur.com/tnXSZoZ.png)

    * 觀察weight
    ![](https://i.imgur.com/Ot09trE.png)

* 每層都做BN
![](https://i.imgur.com/ha7GHMn.png)

* 目前predict的paper embedding都很接近
![](https://i.imgur.com/4MNi5o8.png)

<!-- * top 10 citation paper
![](https://i.imgur.com/4KZcGUr.png) -->

* 推薦paper的id
![](https://i.imgur.com/vxCwT0w.png)

* DeepWalk
    * MAP@1
    ![](https://i.imgur.com/iOLcglo.png)

    * MAP@30
    ![](https://i.imgur.com/UY8waxA.png)

    * MAP@150
    ![](https://i.imgur.com/YWH2E44.png)

* 第一版GraphSAGE
![](https://i.imgur.com/Q6Ehfs7.png)
比Deepwalk的高一點
![](https://i.imgur.com/Y6WaTVa.png)


## BEACON
### 資料處理
![](https://i.imgur.com/Sk7Du60.png)

![](https://i.imgur.com/kRLJiBL.png)
共98001位作者的session data

## LINE
### First Order
![](https://i.imgur.com/okVgXPs.png)
### Second Order
![](https://i.imgur.com/jcJHS4J.png)
### First Order+Second Order
![](https://i.imgur.com/25hM4Ec.png)

 Model concept
![](https://i.imgur.com/pWQCyjc.jpg) -->

