Dive into chat Bot

1. Chat Bot topic summary
Team
FICC Tech macro

2. Self introduction
• Noboru Kano
– 2016 new grad
• Interesting topics
NLP(Natural language processing), Statistics, ML(Machine
learning)
• Experience
1year part time on a start up company as a ML engineer
(Did 3 NLP projects)
• Hobby
Handball, Chinese food, drink party(sometimes), 2ch

3. Agenda
• What is Bot ?
• Chat bot history
• type of chat bot
algorithm and demo
• case study

4. What is Bot ?
• A computer program that simulates human
conversation, or chat, through artificial
intelligence.(From wiki)

5. Why Chat Bot ?
• This year, chat bot has attracted a great deal of
public attention.

6. History of Chat bot
• ELIZA “doctor”(1966)
An early example of primitive NLP chat bot
• A simulation of a psychotherapist.
On your Emacs 

7. • you can find free source about ELIZA in
internet

8. Type of Chat bot
I bought a computer
I like the computer
Hello
Hello I’m kanono !
1. If-then-eles Type
• If the words in dictionaries, bot can respond to you.
• Accuracy depends on the volume of the dictionary
example : ELIZA

9. Type of Chat bot
2. Use dialogue data
Store dialogue data into DB and response a similar message.
• The response would be a human-like message.
• Accuracy depends on the volume of the dialogue
Are you free now?
sorry I’m really busy
That too bad...
What happened?
Are:1, you:1, free:1, now:1
dialogue
DB
ex : パン太一郎

10. Type of Chat bot
3. Generate model
• generate sentence with statistical method.
• calculate the next words appearance ratio.
which dessert do you like the best ?
Yogurt is dessert
I really like frozen yogurt
I watched “Frozen” last night
• Can use variety of phrase and expression
• Difficult to control context in message
Dialogue
corpus
Generate Model

11. Algorithm for Generate model
1. Markov chain
I am John.
I am kanono.
I do not like English
I
do
am
not
0.66
0.33
John
kanono
0.5
0.5
・・・
Strong in make a short sentence.
not good at generating long story.
with large scale corpus data

12. Demo

13. What I made?
Input: Image
Out put: generate a sentence related to the image
Hi ! I’m going to take a
flight to NY training, see
you soon!

14. 技術解説（画像分類部分）
アルゴリズム
1位 aircraft(飛行機)
2位 plane
...
上位10クラスの
スコアを出力
→日本語に翻訳
ラベル

15. 技術解説（ツイート生成部分）
1位 aircraft（飛行機）
ラベル
ラベルに該当する
ツイートをたくさん取得♡
・・・
テキストを自動生成（自作）
今日は飛行機にのるよー！
名古屋みんな待っててね！
ヒミツの自作アルゴリズム♥

16. Algorithm for Generate model
2. RNN(Reccurent Neural Network) ex.) Allo, りんな
RNN for semantic analysis RNN for generate response

17. Case study
• Check my Qiita page
• http://qiita.com/kanottyan/items/2783bf91c8
ea6a8a4ce8