Marko Bohanec - IJSkt.ijs.si/MarkoBohanec/DS2012/DS2012.pdf · Marko Bohanec data Data Mining...

Decision SupportDecision Support

JoJožžef Stefanef Stefan International Postgraduate SchoolInternational Postgraduate School, Ljubljana, LjubljanaProgramme: Programme: Information and Communication TechnologiesInformation and Communication Technologies

Course Web Page: Course Web Page: http://http://kt.ijs.si/MarkoBohanec/DS/DS.htmlkt.ijs.si/MarkoBohanec/DS/DS.html

Marko BohanecMarko Bohanec

Institut Jožef Stefan, Department of Knowledge Technologies, Ljubljanaand

University of Nova Gorica

Marko Bohanec

data

Data MiningData Mining

knowledge discovery from data

decision makers+experts+decision analysts

Decision SupportDecision Support

modelling

model

model

Use of models:

• classification

• clustering

• evaluation

• analysis

• visualization

• explanation

• ...

Decision Making DisciplinesDecision Making Disciplines

Marko Bohanec

Decision Making

Decision SystemsDecision Sciences

Who or what is making decisions?

computerman

• decision theory• utility theory ...

• cognitive sciences• social sciences ...

Decision SupportDescriptiveNormative


Marko Bohanec

Decision Making



computerman

Decision SystemsDecision Systems

Marko Bohanec

Decision Systems

• computers• intelligent programs and systems• robots and autonomous systems

Honda Asimo

Curiosity Mars Rover DARPA Grand Challenge


Marko Bohanec

Decision Making



computerman




Preference RelationsPreference Relations

Preference: we like/desire/prefer one thing over another

Preference relations:

Some properties:

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ba~ indifference

ba≻ strict preference

ba ≻ weak preference

Given any a and b , then ba≻ , ba~ , or ba≺

If ba≻ and cb≻ , then ca≻

If ba~ and cb~ , then ca~

If ba ≻ , then ba≻ or ba~

Utility Theory, Value TheoryUtility Theory, Value Theory

Utility functions (or value functions):

Marko Bohanec

)()(~ buauba =⇔

)()( buauba >⇔≻

Decision TheoryDecision Theory

Decision table:

Types of decisions:

• Certainty: all relevant parameters have known values

• Risk: certain future events have probable outcomes

• (Strict) Uncertainty: impossible to assess the likelihood of future events

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Alternatives

Take umbrella Do not take umbrella

Rains 0.4 0 States

Does not rain 0.9 1

Decision TDecision Treesrees

Decision table:

Decision tree:

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Alternatives

Take umbrella Do not take umbrella

Rains 0.4 0 States

Does not rain 0.9 1

0.4

0.9

0

1

Take

Don’t take

Rain

Rain

No rain

No rain

p=0.8

p=0.8

p=0.2

p=0.2

0.5

0.2

0.5

Further Theoretical AspectsFurther Theoretical Aspects

• Bayesian decision theory

• Multi-attribute utility theory

• Multi-stage problems

• Group decisions

• Game theory

• ...

Marko Bohanec


Marko Bohanec

Decision Making



computerman




Descriptive ApproachDescriptive Approach

Observing how people really make decisions

Herbert Simon: ‘bounded rationality’, ‘satisficing’

• Behavioral Economics

• Cognitive Science:– psychology

– social sciences

– neuroscience

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InterdisciplinarilyInterdisciplinarily on Decision Makingon Decision Making

A. Ule, O. Markič, U. Kordeš (eds.):Konteksti odločanja.Maribor: Aristej, 2009.

Marko Bohanec

INDECS 7(2): Interdisciplinarily on Decision Making.http://indecs.eu/index.php?s=7_2&y=2009

Dan Dan ArielyAriely: Predictably Irrational: Predictably Irrational

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Nobel Prize Winners in EconomyNobel Prize Winners in Economy2007: LEONID HURWICZ, ERIC S. MASKIN and ROGER B. MYERSON

for having laid the foundations of mechanism design theory. 2005: ROBERT J. AUMANN and THOMAS C. SCHELLING

for having enhanced our understanding of conflict and cooperation through game-theory analysis.

2002: DANIEL KAHNEMANfor having integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty.

1994: JOHN C. HARSANYI, JOHN F. NASH and REINHARD SELTENfor their pioneering analysis of equilibria in the theory of non-cooperative games.

1978: HERBERT A. SIMONfor his pioneering research into the decision-making process within economic organizations.

1972: SIR JOHN R. HICKS and KENNETH J. ARROWfor their pioneering contributions to general economic equilibrium theory and welfare theory.

Marko Bohanec


Marko Bohanec

Decision Making



computerman




What is Decision Support?What is Decision Support?

Given the principles of rational decision making,

knowing that decision making can be difficult for people,

can we help the decision makers to make better decisions?

Decision Support:

Providing methods and tools for supporting people in making difficult decisions

How can we support decision making?

Marko Bohanec

MindMind--MapsMaps

Marko Bohanechttp://blog.iqmatrix.com/mind-map/3-new-premium-iq-matrix-mind-maps-released-4

Data Storage, Search and RetrievalData Storage, Search and Retrieval

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Data Cube Pivot Table

Representation and Representation and VisualisationVisualisation ToolsTools

Marko Bohanechttp://paida.sourceforge.net/

Data AnalysisData Analysis

Marko Bohanechttp://www.theintentionexperiment.com/wp-content/uploads/2009/01/trend_analysis_plot_for_ntotalall.bmp

ComputerComputer--Supported Collaborative WorkSupported Collaborative Work

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Central Decision Support DisciplinesCentral Decision Support Disciplines

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Decision Support

Decision AnalysisOperational Research Decision Support Systems

• decision process, stages• modeling• evaluation• finding ‘sufficiently good’

solutions

• mathematical formulation of the decision problem

• searching for optimal solutions

• information systems• decision support• business intelligence

Decision AnalysisDecision AnalysisDecision Analysis: “Applied Decision Theory”

Provides a framework for analyzing decision problems by• structuring and breaking them down into more

manageable parts,• explicitly considering the:

– possible alternatives,– available information– uncertainties involved, and – relevant preferences

• combining these to arrive at “sufficiently good” decisions

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Decision Making and Decision ProcessDecision Making and Decision ProcessDecision:Conscious and deliberate selection of one alternative (option)from a set of possible onesso that it best satisfies the goals of the decision maker.

Decision Making: A process that involves:• identification of the decision problem;• collecting and verifying relevant information;• identifying decision alternatives;• anticipating consequences of decisions;• making the decision;• providing rationale for the decision;• implementing the selected alternative;• evaluating the consequences of the decision.

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Types of DecisionsTypes of Decisions

• Easy (routine, everyday) vs. Difficult (complex)

• One-Time vs. Recurring

• One-Stage vs. Sequential

• Single Objective vs. Multiple Objectives

• Individual vs. Group

• Structured vs. Unstructured

• Tactical, Operational, Strategic

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Types of DecisionsTypes of Decisions

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STRATEGIC

TACTICAL

OPERATIONAL

ORGANISATIONAL LEVELS OF MANAGEMENTSTRUCTURE

OF DECISION PROBLEMS

STRUCTURED

UNSTRUCTURED

STRATEGIC

TACTICAL

OPERATIONAL

ORGANISATIONAL LEVELS OF MANAGEMENTSTRUCTURE

OF DECISION PROBLEMS

STRUCTURED

UNSTRUCTURED

Characteristics of InformationCharacteristics of Information

Properties of information Operational level Strategic level Exactness high low Level of detail detailed aggregated Time span presence future Frequency of use high low Sources inside outside Viewpoint narrow wide Type quantitative qualitative

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Decision Process StagesDecision Process Stages (Herbert Simon)(Herbert Simon)

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INTELLIGENCE• Fact Finding• Problem/Opportunity Sensing• Analysis/Exploration

DESIGN• Formulation of Solutions• Generation of Alternatives• Modelling/Simulation

CHOICE

• Alternative Selection• Goal Maximization• Decision Making• Implementation

Evaluation ModelsEvaluation Models

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EVALUATION

MODEL

EVALUATION

MODEL

options

EVALUATION

ANALYSIS

Examples of DecisionExamples of Decision MModelodelss

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pairwise comparison

multi-attribute model

hierarchical multi-attribute model

Alternative A B C D

A –1 1 0

B 1 1

C –1

D

Weight

Alternative

Attribute

A B C D

10 Salary 8 10 6 5

7 Interestingness 4 8 2 6

5 Location 4 2 9 1

5 Safety 4 6 9 2

4 Image 8 9 7 7

3 Promotion 6 4 8 10

3 Co-workers 2 0 4 8

Evaluation 204 244 228 189

Job

Work

Interestingness Satisfaction

Benefits

Salary Knowledge Other

Promotion Image

Organisation

Location Co-workers Flexibility

Decision Support Research at JSIDecision Support Research at JSI

Decision Supportsupporting people in complex decision-making processes

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• Tools

• Applications

Decision Analysis

Multi-Attribute Modeling

Qualitative Multi-Attribute Modeling

http://kt.ijs.si/MarkoBohanec/dss.html

Decision Support Research at IJSDecision Support Research at IJS

• Methods– Decision Analysis– Qualitative Multi-Attribute Modelling– Data Mining and Decision Support

• Software– DEXi: Multi-attribute decision support

• Applications:– Applications for clients: evaluation of

companies, personnel management, project evaluation, land-use planning, agronomy, medicine and health-care, sport

Hormonalcircumstances

Personalcharacteristics Other

Menstrualcycle Fertility

Oralcontracept.

RISK

Cancerog.exposure

Fertilityduration

Reg. andstab. of men.

Age

First delivery

# deliveries

Quetel'sindex

Familyhistory

Demograph.circumstance

Physicalfactors

ChemicalfactorsMenopause

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ApplicationsApplications

Marko Bohanec

1. Loan Allocation2. Evaluation/Selection of Projects3. Evaluation/Selection of Locations4. Medical Risk Assessment5. Agronomy: GM Crops and Cropping Systems

Allocation of Housing LoansAllocation of Housing LoansHousing Fund of the Republic of Slovenia

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Priority

Ownership

Housing

Present

Suitability

Solving

Work stage

Advantages

Health

Family

Age

Stage

Status

Soc-Health-Social

Earnings

Maint/Employ

Children

Evaluation ofEvaluation of R&D ProjectsR&D Projects

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Environmental: ClayEnvironmental: Clay--Pit LocationPit Location

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2

4

3

1

Legend:

1 Bukovnik

2 Margetnca

3 Existing clay-pit

4 Okroglica

Brick factory

Slovenia

Bohanec, M., Rajkovič, V.: Multi-attribute decision modeling: Industrial applications of DEX, Informatica 23, 487-491, 1999.

ClayClay--Pit Location ModelPit Location Model

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SITE SUITABSITE SUITAB

ATTRACTATTRACT VULNERABVULNERAB

FEASIBILITYFEASIBILITYENVIRONMENTENVIRONMENT

SOC-PSYCHSOC-PSYCH TECHNTECHN ECONOMECONOM

•develop

•site char.

•land attr.

•develop

•site char.

•land attr.

•pollution

•valuation

•land use

•pollution

•valuation

•land use

•transport

•construct

•land org.

•transport

•construct

•land org.

•direct

•indirect

•direct

•indirect

Medicine:Medicine:Breast Cancer Risk AssessmentBreast Cancer Risk Assessment

Hormonalcircumstances

Personalcharacteristics Other

Menstrualcycle Fertility

Oralcontracept.

RISK

Cancerog.exposure

Fertilityduration

Reg. andstab. of men.

Age

First delivery

# deliveries

Quetel'sindex

Familyhistory

Demograph.circumstance

Physicalfactors

ChemicalfactorsMenopause

Bohanec, M., Zupan, B., Rajkovič, V.: Applications of qualitative multi-attribute decision models in health care, International Journal of Medical Informatics 58-59, 191-205, 2000.

Diabetic Foot Risk AssessmentDiabetic Foot Risk Assessment

History Present status Tests

Symptoms Ulcers Amputations

RISK

Other changes Deformities

Loss of prot. sensation

Absence of pulse

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ECOGEN 2003-2006 http://www.ecogen.dk/Soil ecological and economic evaluation of genetically modified crops

EU Projects on GM organismsEU Projects on GM organisms

SIGMEA 2004-2007 http://sigmea.dyndns.org/Sustainable introduction of genetically modified crops into European agriculture

Co-Extra 2006-2009 http://www.coextra.eu/Co-existence and traceabilitiy of GM and non-GM supply chains

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Evaluating cropping systems in terms of ecology, coexistence and economy

Cropping system n

Cropping system 2

Cropping system 1 INPUTS

OUTPUTS

ECOLOGY ECONOMY

MODEL

COEXISTENCE

multi-attribute model

ECOGEN and SIGMEA ModelsECOGEN and SIGMEA Models ““GrignonGrignon”” Model: Ecology PartModel: Ecology Part

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Bohanec, M., Messéan, A., Scatasta, S., Angevin, F., Griffiths, B., Krogh, P.H., Žnidaršič, M., Džeroski, S.:A qualitative multi-attribute model for economic and ecological assessment of genetically modified crops.Ecological Modelling 215, 247-261, 2008.

CONTEXT CROP MANAGEMENT

soil

state

nutrition

state

CROP PROTECTION

weed

control

pest

control

disease

control

weed

profile climate soil farm type

chemical

fertiliz. use

soil

tillage

water

managmt crop

sub-type

biodiversity soil

biodiversity

water

quality

greenhouse

gasses

ECOLOGY

herbivores

pollinators

weed biomass

predators parasitoids indirect

CO2 CO2 N2O

runoff

water

undergrnd

water

pesticide

use

fertilizer

use

fuel

use

herbicide

use

insecticide

use

fungicide

use

physical

stress

physical

disturbance

climatic

disturbance

soil

fertilization

chemical

disturbance

weed ctrl.

applications

““GrignonGrignon”” Model: Economy PartModel: Economy Part

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expected yield

ECONOMY

yields

objective

quality

price

product.

value

CONTEXT

regulatory environment

quality

weed

state

pest

state

YIELD

consumer perc.qual.

technical properties

potential yield

yield strategy

toxines impurity

pesticide costs

seed costs

water costs

labour costs

machinery costs

fertilizer costs

fuel costs

variable

costs

seed

use

water

use

manpower

use

machinery

use

fuel

use

mach+fuel costs

material costs

defficient

nutrition

yield reduction

crop sub-type

nutrition state

CROP MANAGEMENT

chemical

fertiliz. use

fungicide

costs insecticide costs

fungicide

use insecticide use herbicide

use

herbicide costs

AnalyticalMeth

FitForPurposePurposeFitness

FitForExtraction

SiteFitness

Site

FitForOnSiteExtraction

OnSiteExtraction

BestForPurposeConstraints

MethDevelopedDeveloped DevelopementStage

SOP

SuggestedSamples

MethEvaluation

MethPerformance MethPerformance_DNAEx

Yield

DNADNAExtraction

FragmentationDNA

FragmentationHandling

IngredientEffect

StarchStarchEffect

ProteinsProteinEffect

LipidsLipidEffect

SaltSaltEffect

MetalsMetalEffect

Purity

StarchStarchHandling

ProteinsProteinHandling

LipidsLipidHandling

SaltSaltHandling

MetalsMetalHandling

Inhibitors

InhibitorHandlingRobustness

MethApplicability MethApplicabilityExtractionGenerality

SampleHandling

FragmentedDNASamples

LowDNASamples

StarchSamples

ProteinSamples

LipidSamples

SaltSamples

MetalSamples

Costs

BestForDevelopmentConstraints

MethEvaluation MethCosts

FixedCosts

MaterialCostsEquipmentCosts

InfrastructureCosts

NonMaterialCostsCompetenceCosts

ValidationCosts

RunningCosts

Efficiency

Consumables/Sample

Samples/Day

PersonalCosts

DevelopmentCosts

StarchContents

ProteinContents

LipidContents

SaltContents

MetalContents

InhibitorContents

DNAContents

FragmentedSample

Assessment of DNA Analysis MethodsAssessment of DNA Analysis Methods

Marko Bohanec

Decision Support for Data MiningDecision Support for Data MiningFP7 STREP e-Laboratory for Interdisciplinary Collaborative Research

2010-2012 in Data Mining and Data-Intensive Sciences

Rapid Miner’s Workflows(automatically generated)

overallWFassessment

UNDERSTANDABILITY

Interpretability

Familiarity

Complexity

Size

NumNodes

NumEdges

ControlFlow

Interconnectedness

NumPaths

Density

SplitsJoins

Modularity

GraphDegree

AverageGD

MaxGD

ROBUSTNESS

Generality

NoiseSensitivity

Scalability

TIME

Assessment of Workflows(qualitative multi-attribute model)

Other Application AreasOther Application Areas

Marko Bohanec

• Advising in Sports• Business partner selection• Evaluation of technology:

cars, computers, software, Web pages and services, ...• Evaluation of investment proposals, tenders• Production portfolio evaluation• Performance evaluation of companies• Personnel management• Banking: Financial risk indicators• Data Mining: Assessment of workflows• ...

Central Decision Support DisciplinesCentral Decision Support Disciplines

Marko Bohanec

Decision Support


• decision process, stages• modeling• evaluation• finding ‘sufficiently good’

solutions

• mathematical formulation of the decision problem

• searching for optimal solutions

• information systems• decision support• business intelligence

Decision Support Systems (DSS)Decision Support Systems (DSS)

Decision Support Systems:

• interactive computer-based information systems• that support decision-making activities

Characteristics:• DSS incorporate both data and models; • they are designed to assist managers in their decision processes in

semistructured (or unstructured) tasks; • they support, rather than replace, managerial judgment; • their objective is to improve the quality and effectiveness (rather than

efficiency) of decisions.

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Taxonomy of Decision Support SystemsTaxonomy of Decision Support Systems

• A communication-driven DSS supports more than one person working on a shared task

• A data-driven DSS or data-oriented DSS emphasizes access to and manipulation of a data (internal, external, time series, ...)

• A document-driven DSS manages, retrieves, and manipulates unstructured information in a variety of electronic formats

• A knowledge-driven DSS provides specialized problem-solvingexpertise stored as facts, rules, procedures, or in similar structures.

• A model-driven DSS emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation; they are not necessarily data-intensive.

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History of Decision Support SystemsHistory of Decision Support Systemstheory: operational research, decision analysispractice: interactive computers

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1950

1960

1970

1980

1990

2000

first DSSs

specialisation: MIS, EIS, ES, GDSS, ...

data warehouseson-line analytical processing (OLAP)data mining

business intelligenceweb-based DSS

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Traffic Control Traffic Control (Dragomelj)(Dragomelj)

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Traffic ControlTraffic Control

Omerčević, D., Zupančič, M., Bohanec, M., Kastelic, T.:Intelligent response to highway traffic situations and road incidents.Proc. TRA 2008, Transport Research Arena Europe 2008, 21-24 April 2008, Ljubljana.

SMAC AdvisorSMAC Advisor: Decision Support Tool: Decision Support Tool

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SMAC Advisor Wizard User Interface

Co-Existence

Multi-Attribute DEXi Model

MAPOD Simulation Results

1

2

3

SMAC Advisor ArchitectureSMAC Advisor Architecture

SummarySummary

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Decision Making




Marko Bohanec - IJSkt.ijs.si/MarkoBohanec/DS2012/DS2012.pdf · Marko Bohanec data Data Mining...

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