DialogEngines conduct goal-oriented
consulting conversation about given
subjects with individual human users
in pseudo natural language.
Product Model
specifications
properties
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The target domain of the dialog is
an excerpt from an SQL, CSV or XML product
data base. The product knowledge defines
the scope of the dialog.
User Model
explore
understand
find
reassure
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The dialog is with an individual user.
User input to the agent and user answers
to questions by the agent give the
data set which drives the user model.
Base assumption is that the user wants
information about the domain and a specific
solution.
Agent Model
Agents can have different characteristics,
not only age and sex, but
also deeper ones relevant for the progress
of the user interaction. Modelled are
how polite, explanatory, extrovert, pushy
and verbose the agent is. The Agent Model is
independent of its rendering in text, voice
or animation.
Dialog Model
strategy
understanding
initiative
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The dialog consists of repeated listening,
understanding, problem solving, question
asking and result presentation actions.
Dialog history and strategy, together
of course with the product solution space,
define the flow of the dialog.
The dialog produces the control
information for voice and animation.
DialogEngines agents can take initiative
and talk actively to the user.
DialogEngines agents can ask intelligent
questions to the user, taking into account
product knowledge and the context of
the conversation.
Language Model
meaning
ambiguity, contradictions
expressions
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DialogEngines understands user statements
using a shallow natural language processing
model, the target product knowledge, and
additional language knowledge.
Such additional knowledge is domain
expertise and semantics for common
vocabulary. For example the word "small"
will mean different things for different
businesses.
Heuristics are used to resolve ambiguities and
contradictions. DialogEngines is designed to be
practical and useable: like search engines,
which sometimes give wrong answers or not all
correct answers, DialogEngines language
processing is not guaranteed
to be sound and complete.
DialogEngines agents make utterances to users
according to a knowledge base of example
sentences, which can be answers, statements,
greetings, questions, requests for confirmation
and more.
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