This document discusses chatbots and the key technologies behind them. It describes how chatbots are integrated into messaging platforms and examines some of the advantages they provide like low development costs and push notifications. The document outlines two types of chatbots - rule-based and AI-based - and discusses some of the capabilities and challenges of early chatbot technologies like intent recognition and entity extraction. It provides examples of how natural language processing, machine learning, and deep learning are used to power chatbot functions.

1. Chatbots
- - -

2. Chatbot
/ˈtʃatbɒt/
noun
A computer program designed to simulate conversation
with human users to, especially over the Internet.

3. The Rise of Messenger Apps
The race of Chatbots integration on Messaging
platforms is ON!
(MAU: Monthly Active Users)
3www.kooki.co

4. To be more specific
1 Facebook Messenger
2 Slack
3 Telegram
4 Text Messages / iMessage
5 ...
in any major chat products...

5. Why use chatbots?

6. Messaging is the new
browser, and bots are
the new websites.“
“
Mike Roberts, Head of Messaging @ Kik, said this:

7. Development cost
command line chatbot website mobile app

8. Deploying updates
command line chatbot website mobile app

9. Push notifications
command line chatbot website mobile app

10. • Simple to develop
• Asynchronous notifications
• Integrates with team
Chatbot advantages

11. How does it work?
User makes a request Request analyzed
by artificial intelligence
User info taken into account
(history, preferences…)
Real time response
Conversational strategy
Interactions personalization
…

12. TWO TYPES OF CHATBOTS
1. Based on rules
2. Based on Artificial
intelligence

14. Madison Reed

15. Lybrate

16. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #1: Natural Language Processing (NLP)
NLP enables computers to derive meaning from human or natural
language input.

17. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #2: Machine Learning (ML)
ML enables computers to learn when exposed to new data without
being explicitly programmed.

21. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #1: Natural Language Processing (NLP)
NLP enables computers to derive meaning from human or natural
FIRST GENERATION
CHATBOT CAPABILITIES AND
CHALLENGES

22. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #1: Natural Language Processing (NLP)
NLP enables computers to derive meaning from human or natural
Intent Recognition (classification)
“the ability to understand the intent from human ambiguous
language”
#wordvector, #deeplearning4j, #opennlp, #stanfordnlp

23. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #1: Natural Language Processing (NLP)
NLP enables computers to derive meaning from human or natural
Cont,
Advance Intent Recognition Challenge
“The city councilmen refused the demonstrators a permit because they feared violence”
“What does the word “they” refer to here — the councilmen or the demonstrators? What if instead of “feared”
we wrote “advocated”?”(1)
“Oren Etzioni: When AI can’t determine what “it” refers to in a sentence, it’s hard to believe that it will take over
the world”(1)

24. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #1: Natural Language Processing (NLP)
NLP enables computers to derive meaning from human or natural
Cont,
Intent Recognition Training Model Guideline
“intents should be different enough to help the ML disambiguate better”
“Good Pizza vs Bad Pizza are not two different intents, the intent here would be Pizza Quality, Good and Bad would
be entity Rating”
“single keywords are not useful”
“unique sentences are super helpful, semantically and synonym rich”
“do {word} sentence construction in different intent models will falsely give high prediction score for all intents”

25. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #1: Natural Language Processing (NLP)
NLP enables computers to derive meaning from human or natural
Cont,
Entity Recognition (NER)
“the ability to automatically recognize entity meanings from ambiguous language”
“despite all improvements in ML, the problem of accurate entity recognition is far from been solved”
“main effort currently is directed to find approaches to reduce the annotation labor – semi-supervised NER”
#opennlp, #stanfordnlp

26. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #1: Natural Language Processing (NLP)
NLP enables computers to derive meaning from human or natural
Cont,
Entity Recognition (NER) – example with OpenNLP
Model
“The other day at work I saw <START:person> Larry Elison <END> at <START:building> HQ600 <END>”
Test
“The other day at work I saw Lyudmil Pelov at HQ300”
“The other day at work I saw lyudmil Pelov at 300”

27. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #1: Natural Language Processing (NLP)
NLP enables computers to derive meaning from human or natural
Cont,
Sentiment Analysis (emotional intelligence)
“evaluate subjective patterns and expressions of sentiment within textual content”
“usually identifies if expression was positive, negative, mixed, or neutral”
“requires a high degree of supervised ML on big data corpus, usually Twitter”
#deeplearning4j, #opennlp, #stanfordnlp

28. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #1: Natural Language Processing (NLP)
NLP enables computers to derive meaning from human or natural
Cont,
Probabilistic Parser
“probabilistic parsing is using dynamic programming algorithms to compute the most likely parse(s) of a given
sentence, given a statistical model of the syntactic structure of a language”
“parse any address, name, number, date or any unstructured text in useful components”
#stanford, #duckling, #parserator

29. Cont,
…
Text &/or Speech Engine
Natural Language
Processing
Machine and
Deep Learning
AI Engine #1: Natural Language Processing (NLP)
NLP enables computers to derive meaning from human or natural
Cont,
Probabilistic Parser – Duckling Example
#stanford, #duckling, #parserator

30. Movie Usher bot

31. Movie Usher bot
Movie Usher Bot will be your usher in the world of
cinema,it will help you to get your favorite movie,
also it can recommending movies to you based
on your mode or genres,
and it will help you to get information about movies
By the way it is Available now on Messenger :)
…

32. Scenario
…

33. Questions?

34. Thank you :)
Keep Exploring.