oracle digital assistant - github pages
TRANSCRIPT
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Oracle Digital Assistant The Complete Training
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Q&A
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Safe Harbor StatementThe 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, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.
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Topic agenda
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Introducing QnA
Answer intents
QnA and Digital Assistant
Reusable QnA skill
1
2
3
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Topic agenda
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Introducing QnA
Answer intents
QnA and Digital Assistant
Reusable QnA skill
1
2
3
4
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Sometimes a question is what it is; a question
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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”
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Q & A builder• Q & A loaded from a CSV– Category, question, answer
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Q & A builder• Q & A loaded from a CSV– Category, question, answer– Allows matching questions to be browsed
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Q & A at runtime• Intent resolved• Q & A resolved• Could be intent or Q &A
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Q & A at runtime• Intent resolved• Q & A resolved• Could be intent or Q &A
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Q & A at runtime• Intent resolved• Q & A resolved• Could be intent or Q &A
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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...
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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"
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Q & A builder - how it works
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• 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
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Q & A builder - how it works
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Q & A builder - how it works
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Q & A builder - how it works
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Q & A builder - how it works
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Q & A builder - how it works
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Q & A builder - how it works
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Q & A builder - how it works
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Q & A builder - how it works
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Q & A builder - how it works
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>confidenceThreshold
User input phrase
Meets qnaMinimumMatch
Show only intent Show Answer
noyes
Utterance uses imperative
Show QnA and intent
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>confidenceThreshold
User input phrase
Meets qnaMinimumMatch
Show only intent Show Answer
noyes
Utterance uses imperative
Show QnA and intent
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>confidenceThreshold
User input phrase
Meets qnaMinimumMatch
Show only intent
Could be intent or QnA
Show Answer
noyes
Utterance uses imperative
Show QnA and intent
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>confidenceThreshold
User input phrase
Meets qnaMinimumMatch
Show only intent
Could be intent or QnA
Show Answer
noyes
qnaSkipIfIntentFound Show QnA and intent
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>confidenceThreshold
User input phrase
Meets qnaMinimumMatch
Show only intent Show Answer
noyes
Utterance uses imperative
Show QnA and intent
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>confidenceThreshold
User input phrase
Meets qnaMinimumMatch
Show only intent
Unresolved
Show Answer
noyes
Utterance uses imperative
Show QnA and intent
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Q & A routing • Transaction Config– Input is then treated as intent
• Question Config– Ensures QnA shown first in choice
dialog
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Topic agenda
34
Introducing QnA
Answer intents
QnA and Digital Assistant
Reusable QnA skill
1
2
3
4
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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
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Topic agenda
36
Introducing QnA
Answer intents
QnA and Digital Assistant
Reusable QnA skill
1
2
3
4
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Evaluate routing behavior
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Implicit invocation
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Explicit invocation
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Ambiguous utterance
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Non sequitur
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Topic agenda
42
Introducing QnA
Answer intents
QnA and Digital Assistant
Reusable QnA skill
1
2
3
4
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How might you reuse and use multiple QnA within a digital
assistant?
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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
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FinancialBot CorpFinancialBot
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Approach 1: Calling QnA in a different skill
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Demo – Calling QnA in a different skill
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Approach 2: Creating a separate QnA skill in DA
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Shopping Centre Digital Assistant
Digital Bank Skill
Pizza King skill
Shopping center FAQs skill
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Demo – Having a separate QnA skill in DA
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• 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
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Which approach is better?
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Oracle Digital Assistant Hands-On
TBD
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