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OpenWorld 2018 How to Create Chatbots with OMCe

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Presentation on theme: "OpenWorld 2018 How to Create Chatbots with OMCe"— Presentation transcript:

1 OpenWorld 2018 How to Create Chatbots with OMCe
Quick Bite: TRN6509 J. David Mills Cloud Delivery Lead – PaaS Oracle University October 24, 2018

2 Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, timing, and pricing of any features or functionality described for Oracle’s products may change and remains at the sole discretion of Oracle Corporation.

3 Intelligent Chatbots: Key Components
Unified cross-channel chat interface between bots & humans Channel Configurator Dialog Flow Execution Custom Components in Dialog Flow AI Engine Declarative bot builder UI for bot flow State machine that executes context driven workflows with scoped variables Custom SDK to consume backend API’s that satisfy human requests via the bot Active machine learning algorithms that identify relationships and extract insights from unstructured data Develop Intelligent Bots

4 Intent Classification Entity Extraction Dialog Execution
Channel Integration Intent Classification Entity Extraction Dialog Execution Channel Agnostic Webhook Security Message Processing Intent Modeling Natural Language Linguistic Modeling Bot Model Training Entity Parsing Entity Resolution Entity Type Entity Value BotML Dialog Flow Dialog State Built Component Custom Component The balance in your savings account is $ Integration Component Ent data Required Entities: Account Type Entity Values Checking Savings Credit NL Understanding Intent Classification: Balances Intent Ranking Confidence  98% Alexa what’s my balance For which account? Savings Develop Intelligent Bots

5 An Introduction to Intents in Intelligent Chatbots
Single meaning mapped from multiple possible inputs Give it meaningful name Add your own utterances Import & export utterances Train and test the intent Stage 1 processing only as good as your utterances Develop Intelligent Bots

6 Develop Intelligent Bots 1 - 6
See the requirements slide for a description of the steps These settings will be used by Facebook. Develop Intelligent Bots

7 Develop Intelligent Bots 1 - 7

8 Develop Intelligent Bots 1 - 8

9 Develop Intelligent Bots 1 - 9

10 An Introduction to Entities in Intelligent Chatbots
Define an Entity list – value list (airport name) Entity list - Value-list (airport code) Entity list - Value-list (city) Create an entity called Travel Destination Create a derived destination (From) with the preceding word “From” which derives from Travel Destination Create a derived destination (To) with the preceding word “To” which derives from Travel Destination Develop Intelligent Bots

11 Entities Important variable in an intent
Helps add relevance to an intent Built-in DATE, TIME, NUMBER, DURATION etc. Custom Domain/use case specific ToAccount, AccountType, PizzaSize Develop Intelligent Bots

12 Built-in Entities Implicitly exist You must add to the intent
Only parsed for if added to entity Entity can resolve to many values Add multiple entities Develop Intelligent Bots

13 Custom Entities You create Domain-specific entities Value List Derived
ToAccount, PizzaSize, SpendingCategory Value List Derived Entity List Develop Intelligent Bots

14 Dialog flow Manages conversation flow State and context
A conversation with a chatbot usually goes through a particular flow- and you might think of the conversation having different states or context. In chatbots you would typically have a dialog flow which defines what should happen next based on an input State and context What to do based on an input Develop Intelligent Bots

15 Dialog Flow The model for the conversation flow Context Variables
Grouping of variables related to a unit of conversation Variables Data held across a context State The various “units of work” in a dialog Currently defined in BotML Visual flow tool is “work in progress” A conversation with a chatbot usually goes through a particular flow- and you might think of the conversation having different states or context. In chatbots you would typically have a dialog flow which defines what should happen next based on an input Develop Intelligent Bots

16 Dialog Flow Develop Intelligent Bots 1 - 16
Here we an a state called “intent” which gets the first input from the used and passes it to the intent engine, depending on how the intent engine resolved that input, dictates where it goes next. For example, the intent engine worked out this was a Balance intent and so processing should now continue from startBalances Develop Intelligent Bots

17 System Components Interaction components Conditional components
Security Utility components When you want to chatbot to actually do something - such as call a back end service, within Intelligent Bots at least, you use something called components. Intelligent Bots gives you a number of prebuilt components. So Text Output List Intent SetVariable ResetVariable Develop Intelligent Bots

18 Custom Components Custom Components Add custom logic or add features you don't find in a current version Add channel specific UI Backend integration through custom components REST APIs with particular “signature” Communicate with MCS APIs JavaScript However you would typically develop your own custom components for things like making back end calls to APIs (for example, to actually get a bank balance) And a custom component can also have a UI element to it – so if you want to present information to the user as some sort of card component, you could write that yourself Custom Logic Custom UI Backend Integration Develop Intelligent Bots

19 System Settings in Intelligent Chatbots
General General settings for bot processing Training Model Translation Service Channel Connecting bot to channel such as Facebook Develop Intelligent Bots

20 Try Mobile Cloud Service Enterprise Today
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21 Cloud Learning Subscription

22 Q & A Call to Action (time permitting) Learn More @Oracle University
(time permitting) 22

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