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decision support systems Flashcards

1
Q

decision

A

coice made between 2 or more alternatives

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2
Q

decision support systems

A

systems that assist users in making decisions
task oriented (deisgned to address particular problem)
generate alternatives

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3
Q

dss are based on

A

intelligent systems
non-intelligent systems

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4
Q

to assist in decision making it uses (4)

A

models
analytical tools
databases
automated processes

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5
Q

automated processes

A

acheived via intelligent systems with focus on rules and pattern deterntion in data

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6
Q

categories of decision making (3)

A

structured
unstrictured
semi-structured

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7
Q

structured

A

no uncertanities in problem
decision can be made with machine
solution cna be clearly and definitely determined
dss is not required

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8
Q

examples of structured

A

allocating grades to students based on test marks
which borrowers have overdue books
can i afford this house?

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9
Q

semistructured

A

some indication of path to take
dss are most useful
there is a method to follow
requirements are clear cut

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10
Q

example of semistructured

A

will we approve this house loan?

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11
Q

unstructured

A

no clear-cut path to decision
decision require human intuition, feelings emotions and insight
significant or complete uncertanity
no method to reach decision
too many variables
judgements required

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12
Q

example of unstructured

A

will the share price rise?

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13
Q

systems to support decision making (9)

A

spreadsheets
databases
expert systems
nueral networks
data warehouses
ground decision support systems
managemnt informaiton systems
geographical information ysstems
online transaction processing

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14
Q

spreadsheet

A

software applicaiton for manipulatinf numeric data
used in structure decision

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15
Q

databases

A

act as data sources for toher dss tools

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16
Q

expert systems

A

models reasoning of human expert using definite rules
simple if-then rules
query expert system
display rules system used to reach conclusion in both text and as decision tree

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17
Q

examples of expert systems

A

weather forecasting
medical diagnosis
building design

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18
Q

neural networks

A

learns by experience an then applys knowledge to solve new but similar problems
trained by simple data and results
suited to unstructured sistuations
rely on rules and facts experts already know

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19
Q

examples of neural networks

A

OCR
voice recognition

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20
Q

data warehouses

A

act as data source for other dss tools

21
Q

gdss

A

ground decision support systems
multiple users can make decisions
voting systems which automatically tallk results
comments cnabe be made and dsiplayed by participants

22
Q

mis

A

management infromaiton systems
help in structured
summarises data from current databases
privide decision makers with information but are not true in dss

23
Q

gis

A

geographical information systems
display geographic information using maps with multiple layers
manipulate view of data
import local data
graphical display of numerical information

24
Q

oltp

A

online transaction processing
create reports from operational databases fpr use by other dss tools
structure decision
allows users to analyse large data stores online

25
steps in deisnging spreadsheets
creating pen and paper model identifying data sources planning user interface developing formulas to be used knowledge base of if-then rules in an expert system
26
structure of expert system (5)
knowledge base database of facts inference engine explanation mechanism user interface
27
knowledge base
contians rules for system in if-then format can be represented in decision tree format
28
database of facts
contains all facts generated by system during current execution of problem facts are derived by inference engine that is evaluation conditions
29
inference engine
uses facts from database and ruled from knowledge bases to process condition/premise evaluate true/false simulates reasoning of human expert
30
explanation mechanism
considers rules and facts that have been used by system to justify conclusions that system has made prepares output into format user can understand
31
user interface
represents booundary between system and user clear prompts and resposnses communicates final conclusion to user
32
types of inference engines
forward chaing backward chaining
33
forward chaining
starts with facts and uses data to reach new facts/conclusions data-driven strategy no specific goal before execution user may be asked for values is a rule's condition cannor be evaluated
34
backwards chainging
interactively infers facts in conjuntion with user inputs goal driven strategy user asked questions to gather informaiton required to achieve specific goal
35
certanity factor
used to indicate probability of fact/conclusion being true (probability weighing) expert may introduce it into original databse of facts indicates probability of conclusion being correct
36
macros
short user defined command that executes a series of predefined commands used to automate processing
37
data mining
process of discovering non-obvious patterns within large volumes of data (particularly data warehouses) once conclusions have been made future behaviour of systems can be predicted
38
what-if model
considers effects of different inputs
39
olap
online analytical processing provides businesses with statistical evidence to support decision making large data stores are analysed and fast response times are expected users interact with software using olap interface
40
data visualisation
involves data being displayed in a graphical and interactive formal (charts, graphs etc.) make it easier for user to see relationships between data and hence make decisions
41
drill downs
refers to ability to focus on one particular piece of information and to view more and more infroamtion as required by user progress from summary infromation to detailed information
42
collecting
human expert knowledge engineer
43
human expert
through years of experience they have insight into many problems
44
knowledge engineer
observes human expert and gathers data form sources such as databases structures data into appropriate forma and encode knowledge of human expert in series of rules stored in knowledge database
45
storage prcoess
prepares data in fromat that is suitable for storage device data may need to be stored in data warehouse or internet
46
retrieving
process of loading data back onto ram immediately available for processing and display
47
intelligent agent
software application that can be used to automatically perform the processes of stroage and retireval able to adapt behaviour to new user preferences
48
benefits of with dss
preserving expert knowledge improving performance and consistency rapid decisions abilityto analyse unstructured situations
49

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