Intelligent Information Systems Answers Synergy

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Intelligent Information Systems Answers Synergy


Intelligent Information Systems (Synergy Tests) Answers to Excellent Collection of 45 questions
The sum of the confidence factors of the set of values ​​with a relative scale from 0 to 100 ...
belongs to the segment from 0 to 100
always over 100
may be different
always equal to 100
always less than 100

A training sample in which for each example the value of the class-forming feature is explicitly set is called a sample ...
"With the teacher"
“Without teacher”
no correct answer

The extraction of knowledge from data in a self-learning IMS is based on ...
knowledge base
repository
information storage

The process of finding a solution to a problem, which consists in obtaining, based on a set of statements, general statements, is called ...
inductive output
abductive inference
deductive inference

The semantic network is ...
set of classes and objects of the subject environment
data structure designed to represent some standard situation
a model that allows you to represent knowledge in the form of sentences like "IF (condition), THEN (action)"
oriented graph whose vertices are concepts and arcs are the relationships between them

The concept of uncertainty of knowledge includes ...
Several variants:
variability
incompleteness
polysemy
unreliability
quality ratings

The expert system consists of ...
knowledge base
intelligent interface, knowledge base and conclusion mechanism
smart interface
conclusion mechanism

A self-learning IP, which, based on training based on real-life examples, builds a network of transfer functions, is called ...
neural network
use case system
inductance system

Development of a knowledge base in the language of knowledge representation is ...
conceptualization of knowledge
implementation
knowledge identification
formalization of knowledge

The implementation phase of the expert system is ...
no correct answer
setting up and finalizing a software tool
setting up and finalizing a software tool, filling the knowledge base
filling the knowledge base

Filling the ES knowledge base is ...
formalization of knowledge
knowledge identification
implementation

The formalization of knowledge is ...
development of knowledge base in the language of knowledge representation
obtaining by the knowledge engineer the most complete possible representation of the subject area and
decision making methods in it
prototype ES
development of an informal description of domain knowledge in the form of a graph, table, chart or text

The user is ...
specialist engaged in the extraction of knowledge and their formalization in the KB
specialist whose knowledge is placed in the knowledge base
specialist whose intellectual abilities are expanded through the use of ES

The development of a description of the structure of knowledge about the subject area in the form of a graph, table, diagram or text is ...
conceptualization of knowledge
knowledge identification
formalization of knowledge
implementation

A knowledge engineer is ...
specialist whose knowledge is placed in the knowledge base
specialist engaged in the extraction of knowledge and their formalization in the KB
specialist whose intellectual abilities are expanded through the use of ES

The conceptualization of knowledge is ...
development of a description of the structure of knowledge about the subject area in the form of a graph, table, diagram or text
development of knowledge base in the language of knowledge representation
obtaining by the knowledge engineer the most complete possible representation of the subject area and
decision making methods in it
prototype ES

Establish the order of the stages of designing an expert system
problem area identification
conceptualization of the problem area
formalization of the knowledge base
implementation of an expert system
expert system testing

As a result of inductive inference is being built ...
goal tree
decision

Additional information

Systems with an intelligent interface include ...
cognitive graphics systems
use-case systems
intelligent databases
hypertext systems
application programs

Identification of knowledge is ...
prototype ES
domain parameterization
development of an informal description of domain knowledge in the form of a graph, table, chart or text
development of knowledge base in the language of knowledge representation

The mechanism for the conclusion of conclusions in an expert system can be implemented using ...
forward and reverse chain of reasoning
reverse chain of reasoning
direct chain of reasoning
forward or reverse chain of reasoning

Participates in the creation of ES ...
knowledge engineer
customer and expert
customer, expert and knowledge engineer
expert
expert and knowledge engineer
user
customer

The difference between synthetic and dynamic expert systems is ...
handling uncertainty of knowledge
reactions to events
using multiple sources of knowledge

Choose the most accurate knowledge base definition ...
set of decision rules
set of knowledge units reflecting facts and dependencies of facts
set of object names and their relationships
Associations arise ...
in the simplest neural networks
in populations of unicellular organisms
in hierarchical structures to maintain material and discard non-material information

The training sample consists of ...
no correct answer
examples of artificial situations generated by enumerating all possible options for the development of events, described by many signs of classification
examples of real situations accumulated over a certain historical period are described by many signs of classification
classification features used to describe possible scenarios

Match
Answer Type: Match
A. use-case systems
B. Hypertext systems
C. multi-agent systems

D.Systems with smart interface
E. Systems with access to various sources of knowledge
F. Self-learning IP

The process of learning a neural network comes down to determining ...
the number of neurons in the intermediate layer
the number of neurons in the entire network
neuron link weights
the number of input signals (features)

The rule for building a goal tree is not ...
all the vertices of the lower level obey all the vertices of the higher level hierarchy
all vertices of the lower level obey one vertex of the higher level of the hierarchy
the top of the lower level obeys only one top of the higher level of the hierarchy

A self-learning IP that allows you to extract knowledge from databases and create specially organized knowledge bases is ...
expert system
data mining system
intelligent system

At the stage of testing the expert system, the knowledge engineer and expert play the following roles ...
knowledge engineer - active, expert - passive
knowledge engineer - passive, expert - active
both play an active role
both play a passive role

A lot of software tools and experts for joint solution of tasks operating in a single distributed computing environment - is ...
knowledge management system
DBMS
information retrieval system

A - F
B - E
C - D

Intelligent Databases - Intelligent Interface Systems
Dynamic Systems - Expert Systems
Neural Networks - Self-Learning ICs

A multi-agent systems - F Systems using various sources of knowledge
B Systems with cognitive graphics - D Systems with an intelligent interface
C Neural Network Systems - E Self-Learning ICs


Information is ... New and Useful Problem Solving Facts
Knowledge is ... Facts accepted by the subject and their dependencies, remembered for subsequent use
Data is ... Facts recorded on any medium
A - d
B - f
C - E

Context Aid Systems - Intelligent Interface Systems
Inductive Systems - Self-Learning ICs
Classification Systems - Knowledge Based Systems

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