關鍵字的應用身處於每個人的日常生活及企業應用之中，舉凡欲尋找有關沖繩相關旅遊資訊該如何下出正確的關鍵字， 或者是你是個廣告業務想要投放嬰兒用品的廣告不知道該下哪些關鍵字。這時你會需要打造一個關鍵字精靈來協助你 演講內容會介紹 Text Mining 的一些基本觀念、打造關鍵字聯想精靈的技巧及所需要套件資源，最後會介紹一些實際的應用。

1. 如何建置關鍵字精靈
How to Build an Keyword
Wizard

2. Agenda
● What is Keyword ?
● Why We Need ?
● Word Relation & Word Representation
● How to Build this Wizard
● Live Demo

3. What is Keyword ?
● Wikipedia : Keyword (computer programming), word
or identifier that has a particular meaning to the
programming language

4. Why We Need ?
Advertisement Tags
Look Me !
Relation Article Summary

5. Word Relation Model
琉球潛水
沖繩潛水
沖繩機場
那霸機場
琉球機場
琉球浮潛
沖繩浮潛
沖繩水族館
琉球水族館
OKinawa 水族館
沖繩

6. Word Relation Model
沖繩

7. Word Representation - Vector Space Model

8. One Hot v.s Continue Value
It is better for
analysis
Very High
Dimension

9. Word Representation - One Hot Representation
Word One Hot Index
Apple 00000001
how 00000010
Are 00000100
You 00001000
I 00010000
Am 00100000
Fine 01000000
Book 10000000
How Are You ? I am Fine . Thank You
TF - Term Frequency
01111110
00001000
00010000
AND
You
I
00000000

10. Word Representation - Context Vector
P(Wi|Context)
Word 餐廳 浮潛 美食 旅遊 出國
沖繩 0.1 0.7 0.5 0.9 0.5
好吃 0.6 0.01 0.7 0.01 0.02
Okinawa 0.2 0.5 0.2 0.8 0.7
喔伊西 0.3 0.002 0.8 0.02 0.03
Similar
Similar

11. Word Context Vector

12. Co-occurrence Matrix
Sparse & Large
n ~= 500K
Space ~= n*n
Time ~= n*n
GG!!

13. Word2Vec
使用類神網路來產生以下模型：
給予短句中的前文即可預測出下一
個可能會出現的詞
附帶產生的結果
投影層即為詞向量(Word Vector)
https://www.tensorflow.org/versions/r0.8/tutorials/word2vec/index.html
我想要去沖繩潛水 潛水
打
球
潛
水
睡
覺
洗
臉
...

14. Word2Vec
● Google 2013 Release
● Open Source Project
● Two Layer Neural Network
● Another Toolkit : Gensim
● pip install --upgrade
gensim
https://www.tensorflow.org/versions/r0.8/tutorials/word2vec/index.html

15. How to Hands On ???

16. Major Process Flow
Word Collection
Content ExtractionArticle Selection Build ModelWord Cutting
花笠麵很好吃
花笠麵△很△好吃
Slack IntegrationSearch Log

17. Article Selection
High Quality 500K
Articles at 2015Q3Q4
4.4 Billion
Spam
Classifier
Ranking
● pip install --upgrade https://storage.googleapis.
com/tensorflow/linux/cpu/tensorflow-0.8.0-cp27-none-
linux_x86_64.whl
● pip install -U scikit-learn
● http://www.wildml.com/2015/11/understanding-
convolutional-neural-networks-for-nlp/

18. Content Extraction
Top
Content Body
Bottom
Side
Side
<div>
<p>沖繩哪裡好玩</p>
<p>美ら海水族館</p>
<div>
沖繩哪裡好玩
美ら海水族館
● pip install beautifulsoup4

19. Content Extraction

20. Content Extraction

21. Article Raw Data Preparation
A
A1A2A3A4A5A6A7A8A9
B1B2B3B4B4B6B7B8B9
Z1Z2Z3Z4Z5Z6Z7Z8Z9
…..
A1 A2 A4 A5 A6 A7 A8 A9
B1 B2 B3 B4 B6 B7 B8 B9
Z1 Z2 Z3 Z4 Z5 Z6 Z7 Z8 Z9
…..

22. Build Model - Word2Vec

23. Build Model - Word2Vec

24. Build Model - CoOccurrence

25. Term Database
● Search Log
● 各大電商網站(e.q 阿里巴巴)
○ Link1
○ Link2
● http://baseterm.com/
● 輸入法詞庫
○ 詞庫 破解

26. Term Database - Search Log
Term CollectionSearch History
Filter
&
Counting

27. Search Log
Keyword URL Date Click
好吃 http://xxx.xxx 20160520 33
好吃 http://zzz.zzz 20160520 22
日本旅遊 http://xxx.xxx 20160521 15
http://xxxx.xx.xxx http://xxxx.xx.xxx 20160522 12121

28. Term Database - Search Log by Count

29. Term Database - Search Log by Count/Len

30. Term Database
● 各大電商網站(e.q 阿里巴巴)
○ Link1
○ Link2

31. Word Cutting
● Word Cut Tool
○ Jieba : https://github.com/fxsjy/jieba
○ https://github.com/yanyiwu/cppjieba-serve
● C++ Jieba Server ↑ x 30 以上
● pip install jieba

32. Slack Integration
● Library
○ pip install slackbot
○ pip install slacker
● Get Bot Token
○ https://my.slack.com/services/new/bot

33. NAS
Technology Software Stack
Redshift BigQuery Article DB
Spark
WorkerWorker Worker
Jieba Server
Gensim
Word2Vec
Flask
Jupyter
Scikit
Learn
TensorFlow
Slack Bot

34. LIVE Demo

35. Q&A

36. 2016 PIXNET HACKATHON
8/13