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Topic agenda

Introducing QnA

Answer intents

QnA and Digital Assistant

Reusable QnA skill

Topic agenda

Introducing QnA

Answer intents

Reusable QnA skill

Sometimes a question is what it is; a question

Q & A builder• Intent resolution – sentence level resolution– Trying to establish meaning from a sentence–Meaning and structure are important–Maps to a single transaction/usecase

• QnA – word level resolution– Uses an intelligent search across questions and answers– Can be tuned to define Q&A terms and stop words

• “Lost my bank details, need to reset password”• “Can I return these shoes”

Q & A builder• Q & A loaded from a CSV– Category, question, answer

Q & A builder• Q & A loaded from a CSV– Category, question, answer– Allows matching questions to be browsed

Q & A at runtime• Intent resolved• Q & A resolved• Could be intent or Q &A

Q & A routing is based on• The results of intent and QnA matching– Intent resolution–Minimum match of QnA

• Use of imperative verbs assumes intent– “do”, “give” “cancel”• Platform understands the concept of imperative verbs• You can explicitly define your own

• More later...

Q & A routing is based on• qnaMinimumMatch in System.Intent• Defines % of tokens that must match– E.g. 50%, 25% means we first of all look for 50% of matches, if not, we look for 25% -

thus trying to ensure we only drop to 25% if we can’t resolve to a higher quality

• Token is not necessarily a word– Stop words are ignored– Tokens are generated for word pairs• "Balance in my checking account" and "Checking balance in my account", then search for "checking

account" will return "Balance in my checking account"

Q & A builder - how it works

• Smart” logic to search/index– Automatically stems words when indexing• “festival”, “festive”, “festivity” all represented as the same stem

– Ignores stop words (“a”, “of”, “are” etc)– Fuzzy matching (tolerant of one or two char differences)– Define synonyms and abbreviations

>confidenceThreshold

User input phrase

Meets qnaMinimumMatch

Show only intent Show Answer

Utterance uses imperative

Show QnA and intent

User input phrase

Show QnA and intent

User input phrase

Show only intent

Could be intent or QnA

Show Answer

Show QnA and intent

User input phrase

Show only intent

Could be intent or QnA

Show Answer

qnaSkipIfIntentFound Show QnA and intent

User input phrase

Show QnA and intent

User input phrase

Show only intent

Unresolved

Show Answer

Show QnA and intent

Q & A routing • Transaction Config– Input is then treated as intent

• Question Config– Ensures QnA shown first in choice

dialog

Topic agenda

Introducing QnA

Answer intents

Reusable QnA skill

Answer intents• QnA styles of questions can be modelled as intents– Aim to resolve sentence level “understanding” rather than

simply search– “One turn” – displays answer only then completes state – No YAML required

• Like intents, has to be trained with at least 5 utterances• Switch on optimize for answer intents– Found under skill settings

Topic agenda

Introducing QnA

Answer intents

Reusable QnA skill

Evaluate routing behavior

Implicit invocation

Explicit invocation

Ambiguous utterance

Non sequitur

Topic agenda

Introducing QnA

Answer intents

Reusable QnA skill

How might you reuse and use multiple QnA within a digital

assistant?

Options for how you might use QnA• Each skill has its on QnA as required–Modular and simplest option

• Calling QnA in a different skill– Route to a specific QnA based on conversation context– Using the botName and QnaBotName properties that belong to System.Intent and

System.Qna component

• Separate QnA only skill used by the DA– FAQ (QnA skill) may be shown upfront in welcome message–QnA maintained in single place without impacting other skills

FinancialBot CorpFinancialBot

Approach 1: Calling QnA in a different skill

Demo – Calling QnA in a different skill

Approach 2: Creating a separate QnA skill in DA

Shopping Centre Digital Assistant

Digital Bank Skill

Pizza King skill

Shopping center FAQs skill

Demo – Having a separate QnA skill in DA

• Calling QnA in different Bot–More Flexibility: BotML coding

required, hence more control to the user the way he/she wants to invoke QnA

• Creating separate QnA only skill and consuming in DA–QnA skill will be shown upfront in

welcome message!– No additional code required since the

routing will be managed by DA

Which approach is better?

Oracle Digital Assistant Hands-On

Oracle Digital Assistant - GitHub Pages

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