Decision Support Systems Flashcards

1
Q

What is Data management

A

it is used to collect and organise the data

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2
Q

What is model management

A

it involves the use of a model to turn data into information.

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3
Q

What is dialogue management

A

It allows the user to enter a request in a convenient manner. It provides the interactivity of DSSs.

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4
Q

what is a Geographic information system (GIS for short)

A

it is an information system that is capable of assembling, storing, manipulating and displaying geographically referenced information.

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5
Q

What is “What-if”

A

it is the process of making changes to the data and observing their effects.

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6
Q

what are Expert systems

A

they are systems that provide information and solve problems that would otherwise require a person experience in that field to do.

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7
Q

what are the components of an expert system

A

The knowledge base and the inference engine

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8
Q

What is a knowledge base

A

The knowledge base is a set of general facts and if-then rules supplied by an expert.

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9
Q

what is a nerual network

A

it is an information system that works like the human brain and is capable of learning.

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10
Q

what are Expert system shells

A

they are ready-made expert systems except that they contain no knowledge.

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11
Q

what is the database of facts

A

is the data that relates to the specific situation being anaysed.

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12
Q

what is the difference between a database of facts and a knowledge base

A

a knowledge base contains data that are more general where as a database of facts would contain data from a specific problem.

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13
Q

what is an inference engine

A

The inference engine is the part of the expert system that carries out the reasoning. It is essentially a rule interpreter whose function is to use the if-then rules of a knowledge base to solve the problem set by the user.

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14
Q

what is the explanation mechanisim

A

it is a method of checking how the expert system inferred its deduction.

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15
Q

what are the two main types of inference engines

A

Forward chaining and backward chaining

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16
Q

what is forward chaining

A

Forward chaining is an inference strategy in which the user supplies all the data before the question is asked or the inference is made. It begins with data and works forward to see if any conclusions can be reached. They are often used when there is no clear goal and the system is just attmeping to determine all of the conclusions implied by the data.

17
Q

What is backward chaining

A

Backward chaining starts with one or more possible solutions and searches back through the system to determine the questions to be asked. Backward chaining starts with a tentative conclusion and searches back through the rules for the questions or facts that support that conclusion. Backward chaining works in the opposite direction to forward chaining. example is “you are on a healthy diet” and then asks all the questions to ensure the user meets the conditinos.

18
Q

what is fuzzy logic

A

it describes the vairables that exist between a “true” and a “false”. They may be expressed as probabilities or possibilities.

19
Q

What are intelligent agents

A

they are pieces of software that are used in data mining to search through relational databases for relevant data.

20
Q

what is a pivot table

A

it is an interactive table that quickly summarises large amounts of data.

21
Q

what is a linear regression model

A

it is the best-fit relationship between two types of data.

22
Q

what are the types of charts

A

Bar charts

Coloumn charts

line charts

Pie charts

23
Q

what is a chart

A

it is a graphical representation of numerical data

24
Q

when would you use each type of charts

A

Bar charts and column charts are used to do comparisions between items to be made at a glance and show variation between them over a period of time.

Line charts are used to show trends or changes in data over a period of time, and emphasises the time flow/rate of change rather than the amount of change.

Pie charts are used to show the relationship, or proportions of parts to a whole. They are used to appeal to people because they are easy to read and attractive.

25
Q

what is data matching

A

it invovles finding data and giving some meaning to it.

26
Q

how does data matching work in different DSSs

A
  • a database involves searching and sorting data. It requires the user to construct an appropriate query and interpret the results. Data matching in a data warehouse is achieved using data mining. It finds relationships and patterns in the data stored in a database.
  • a neural network is achieved by finding relationships between sets of data to develop an understanding of the situation. They examine the data and create new information as they are training.
  • an expert system involves the use of a knowledge base, a database of facts and an inference engine. The knowledge base and database of facts contain all the data, and the inference engine carries out the reasoning by using the facts, assumptions, theories, and rules.
27
Q

what is primary source

A

it is when data is collected first hand

28
Q

what is secondary source

A

it is when data is collected or created by someone else.

29
Q

what is structured data

A

it is predefined characters, usually numbers, whose meaning and format is specified. It is easily stored and retrieved in an orderly manner for decision-making

30
Q

What is unstructured data

A

Unstructured data does not fit a predefined or descriptive model. It includes all types of media, such as text, audio, numbers, images and video. Unstructured data is more difficult to use in DSSs as it creates greater processing and storage demands.

31
Q

what is the role of an expert in an Expert system

A

The expert supplies the knowledge for the knowledge base and the inference engine. The quality of an expert system is dependent on the knowledge of the expert.

32
Q

what is the role of the knowledge engineer in the expert system

A

Knowledge engineers are the people who build the expert system. They are responsible for obtaining information from the human experts and for designing the structure of the knowledge base and the inference engine.

33
Q

What is a group decision support system

A

GDSS for short, It is an information system that assists users to make a decision by working together in a group

34
Q

what are the five main features of GDSS

A

presentation material

commenting

brainstorming

voting

evaluation

35
Q

What is a macro

A

A macro is a series of commands stored in a file that can be executed by pressing a few keys. Macros allow many operations to be performed automatically, such as opening menus, choosing commands or entering text