DN 2017 | Generative models for chatbots | Karol Przystalski | Codete

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Karol explains shortly different aspects of machine learning methods used for bots. The topics that are covered during this session are natural language understanding, sentiment analysis, conversation management and pattern recognition. The main part is dedicated to generative models that are the current trend when it comes to chatbots. A taxonomy of generative models is presented. The presentation is concluded with an explanation on how to use deep learning methods to extend a chatbot to be more intelligent.

Data & Analytics

Dr. Karol Przystalski
Generative models for chatbots

Current chatbots challenges
Context Management
Sentiment Analysis
Pattern Recognition
Natural Language Understanding
Designing Bots, Amir Shevat, O’Reilly 2017

Current approches
Rule-based
Retrieval-based
Generative-based

Rule-based
Phrases list
Show status of recruitment.
What is the weather in Berlin?
Hi!
Hire candidate <name>.
No valid phrase found
Answers list
We have currently X candidates.
It is <current weather>.
Hi. How are you?
Sent an email to <email>.

Rule-based
Bottlenecks/Challanges
⟶ too simple for most cases
⟶ not really intelligent
Advantages
✓ is predictable
✓ clear principles
✓ cheap

Retrieval-based
Advantages
✓ identify the intent
✓ usually easy to train
✓ does not need too many
questions/answers
✓ more intelligent than rule-based
Bottlenecks/Challanges
⟶ limited to questions/answers

Generative-based
Advantages
✓ generic, intelligent answers
✓ raw data
Bottlenecks/Challanges
⟶ usually takes longer to train
⟶ need a data set that is usually huge
⟶ sometimes unpredictable

Comparison
⟶ don’t use a solution/approach because it’s cool!
⟶ in many cases classic machine learning methods are good enough and
generative models does not need to be used
⟶ generative models are good if we are looking for a more generic solution and
have a lot of data to be used for training

Where to go next ...
To learn more about bots and how build one, please register for Developing
bots primers workshop: workshops.codete.com. It’s free.
Read Pattern recognition Primer, Springer 2018 book. It will be published in
Spring 2018.
Looking for ideas or advices? Find me at our booth at Data Natives conference.

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