knowledge engineering oxford 17 02 10 natarajan

8/2/2019 Knowledge Engineering Oxford 17 02 10 Natarajan

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Knowledge Engineering

Lecture delivered by

Dr S.Natarajan

Professor , Dept of ISE, PESIT,Bangalore

Session Chair

forNational Conference on Optimization of IT

Oxford College of Engineering, Bangalore

on February 17,2010


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1. Background

What Is Knowledge?

Data

A Record of a

Change of

State

1840KL0617

Information

The flight from Delhi

leaves at 18:40 hours

Dataorganized with

a purpose. Amessage

Knowledge

thats not a good

flight; Often busyand delayed

Literally

what people

know


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Introduction 3

Knowledge engineering

process of eliciting,

structuring,

formalizing,

operationalizing

information and knowledge involved in a knowledge-intensive problem domain,

in order to construct a program that can perform adifficult task adequately


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Ontology

An ontology is a formal representation of a set of concepts within adomain and the relationships between those concepts. It is used toreason about the properties of that domain, and may be used to definethe domain

In theory, an ontology is a "formal, explicit specification of a sharedconceptualisation. An ontology provides a shared vocabulary, which

can be used to model a domain that is, the type of objects and/orconcepts that exist, and their properties and relations

Ontologies are used in artificial intelligence, the Semantic Web,systems engineering, software engineering, biomedical informatics,library science, enterprise bookmarking, and information architecture as

a form of knowledge representation about the world or some part of it. The creation of domain ontologies is also fundamental to the definition

and use of an enterprise architecture framework.

Introduction 4
http://en.wikipedia.org/wiki/Domain_of_discoursehttp://en.wikipedia.org/wiki/Reasoninghttp://en.wikipedia.org/wiki/Artificial_intelligencehttp://en.wikipedia.org/wiki/Semantic_Webhttp://en.wikipedia.org/wiki/Systems_engineeringhttp://en.wikipedia.org/wiki/Software_engineeringhttp://en.wikipedia.org/wiki/Biomedical_informaticshttp://en.wikipedia.org/wiki/Library_sciencehttp://en.wikipedia.org/wiki/Enterprise_bookmarkinghttp://en.wikipedia.org/wiki/Information_architecturehttp://en.wikipedia.org/wiki/Knowledge_representationhttp://en.wikipedia.org/wiki/Enterprise_architecture_frameworkhttp://en.wikipedia.org/wiki/Enterprise_architecture_frameworkhttp://en.wikipedia.org/wiki/Knowledge_representationhttp://en.wikipedia.org/wiki/Information_architecturehttp://en.wikipedia.org/wiki/Enterprise_bookmarkinghttp://en.wikipedia.org/wiki/Library_sciencehttp://en.wikipedia.org/wiki/Biomedical_informaticshttp://en.wikipedia.org/wiki/Software_engineeringhttp://en.wikipedia.org/wiki/Systems_engineeringhttp://en.wikipedia.org/wiki/Semantic_Webhttp://en.wikipedia.org/wiki/Artificial_intelligencehttp://en.wikipedia.org/wiki/Reasoninghttp://en.wikipedia.org/wiki/Domain_of_discourse


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G.Tecuci, Learning Agents Laboratory

How are agents built

A knowledge engineer attempts to understand how a subject

matter expert reasons and solves problems and then encodesthe acquired expertise into the agent's knowledge base.

The expert analyzes the solutions generated by the agent(and often the knowledge base itself) to identify errors, andthe knowledge engineer corrects the knowledge base.

Knowledge

Engineer

Domain

Expert

Knowledge Base

Inference Engine

Intelligent Agent

Programming

Dialog

Results


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Introduction 6

Problems in knowledgeengineering

complex information and knowledge is difficult toobserve

experts and other sources differ

multiple representations: textbooks

graphical representations

heuristics

Skills

A study carried out in 1989 showed that the main reason whyexpert systems were not being used was an insufficiency ofmethods for development, especially in the construction ofknowledge bases, e.g. the transfer of expertise.


7/66Introduction 7

Importance of properknowledge engineering

Knowledge is valuable and often outlives a particularimplementation knowledge management

Errors in a knowledge-base can cause seriousproblems

Heavy demands on extendibility and maintenance changes over time


8/66Introduction 8

A Short History ofKnowledge Systems

1965 19851975 1995

general-purposesearch engines

(GPS)

first-generationrule-based systems

(MYCIN, XCON)

emergence ofstructured methods

(early KADS)

maturemethodologies

(CommonKADS)

=> from art to discipline =>


9/66Introduction 9

First generation Expert

Systems

shallow knowledge base

single reasoning principle

uniform representation

limited explanation

capabilities

reasoningcontrol

knowledgebase

operateson


10/66 G.Tecuci, Learning Agents Laboratory

Defining problem to solve and system to be built:requirements specification

Choosing or building an agent building tool:Inference engine and representation formalism

Development of the object ontology

Development of problem solving rules or methods

Main phases of the agent development process

Refinement of the knowledge base

Feedbackloops

among allphases

Understanding the expertise domain



A knowledge engineer is assigned the job of buildingthe system.

The knowledge engineer becomes familiar with the problem

and the domain.

The knowledge engineer finds an expert on the subjectwho agrees to collaborate in building the system.

Investigated solution

Develop a computer system that incorporates the expertiseof people familiar with spill detection and containment(i.e. a knowledge-based system, expert system or agent).



By eliciting the expert's conception of his/herexpertise domain we mean determining whichconcepts apply in the domain, what they mean,

what is their relative place in the domain, what arethe differentiating criteria distinguishing thesimilar concepts, and what is the organizationalstructure giving these concepts a coherence forthe expert.

Elicitation of experts conception of a domain



(based primarily on Gammack, 1987)

Elicitation methodology

1. Concept elicitation: methods(elicit the concepts of the domain i.e. anagreed vocabulary)

2. Structure elicitation: the card-sort method(elicit some structure for the concepts)

3. Structure representation(formally represent that structure in asemantic network)

4. Transformation of the representation(transform the representation to be used forsome desired purpose)


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Introduction 14

Transfer View of KE

Extracting knowledge from a human expert mining the jewels in the experts head

Transferring this knowledge into KS.

expert is asked what rules are applicable translation of natural language into rule format


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Introduction 15

Problems with transfer view

The knowledge providers, the knowledge engineerand the knowledge-system developer should share a common view on the problem solving process and

a common vocabulary

in order to make knowledge transfer a viable way ofknowledge engineering


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Introduction 16

Rapid Prototyping

Positive focuses elicitation and interpretation

motivates the expert

(convinces management)

Negative large gap between verbal data and implementation

architecture constrains the analysis hence: distorted model

difficult to throw away


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Introduction 17

Methodological pyramid

world view

theory

methods

tools

use feedbackcase studies

application projects

CASE tools

implementation environments

life-cycle model, process model,

guidelines, elicitation techniques

graphical/textual notations

worksheets, document structure

model-based knowledge engineering

reuse of knowledge patterns


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Introduction 18

World view: Model-Based KE

The knowledge-engineering space of choices andtools can to some extent be controlled by theintroduction of a number of models

Each model emphasizes certain aspects of thesystem to be built and abstracts from others.

Models provide a decomposition of knowledge-engineering tasks: while building one model, theknowledge engineer can temporarily neglect certainother aspects.


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Introduction 19

CommonKADS principles

Knowledge engineering is not some kind of `miningfrom the expert's head', but consists of constructingdifferent aspect models of human knowledge

The knowledge-level principle: in knowledgemodeling, first concentrate on the conceptualstructure of knowledge, and leave the programmingdetails for later

Knowledge has a stable internal structure that isanalyzable by distinguishing specific knowledgetypes and roles.


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KADS

Introduction 20

Knowledge Acquisition and Documentation Structuring(KADS) is a structured way of developing Knowledge-BasedSystems (KBS)(Expert Systems).

It was developed at the University of Amsterdam as an

alternative to an evolutionary approach and is now accepted asthe European standard for KBS

Its components are:

A methodology for managing knowledge engineering projects.

A knowledge engineering workbench.

A methodology for performing knowledge elicitation.

KADS was further developed into CommonKADS
http://en.wikipedia.org/wiki/Knowledge-based_systemshttp://en.wikipedia.org/wiki/Knowledge-based_systemshttp://en.wikipedia.org/wiki/Expert_systemhttp://en.wikipedia.org/wiki/University_of_Amsterdamhttp://en.wikipedia.org/wiki/University_of_Amsterdamhttp://en.wikipedia.org/wiki/Expert_systemhttp://en.wikipedia.org/wiki/Knowledge-based_systemshttp://en.wikipedia.org/wiki/Knowledge-based_systemshttp://en.wikipedia.org/wiki/Knowledge-based_systemshttp://en.wikipedia.org/wiki/Knowledge-based_systems


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KADS (contd)

Knowledge Based Systems Analysis and DesignSupport (KADS) originating in the European ESPRITproject P1098

75 men-years of work, was one of the most highlydeveloped KBs (Knowledge Based Systems) in theearly 90s.

Introduction 21


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KADS (contd)

This pioneering method provides two types ofsupport for the production of KBs in an industrialapproach:

firstly, a lifecycle enabling a response to be madeto technical and economic constraints (control of theproduction process, quality assurance of thesystem,...), and

secondly a set of models which structure theproduction of the system, especially the tasks ofanalysis and the transformation of expert knowledgeinto a form exploitable by the machine.

Introduction 22


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Introduction 23

CommonKADS theory

KBS construction entails the construction of anumber of models that together constitute part of theproduct delivered by the project.

Supplies the KBS developer with a set of model

templates. This template structure can be configured, refined

and filled during project work.

The number and level of elaboration of models

depends on the specific project context.


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Introduction 25

Model Set Overview (1)

Organization model supports analysis of an organization,

Goal: discover problems, opportunities and possibleimpacts of KBS development.

Task model describes tasks that are performed or will be performed in

the organizational environment

Agent model describes capabilities, norms, preferences and permissions

of agents (agent = executor of task).


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Introduction 26

Model Set Overview (2)

Knowledge model gives an implementation-independent description of

knowledge involved in a task.

Communication model models the communicative transactions between agents.

Design model describes the structure of the system that needs to be

constructed.


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Introduction 27

Principles of the Model Set

Divide and conquer.

Configuration of an adequate model set for a specificapplication.

Models evolve through well defined states.

The model set supports project management. Model development is driven by project objectives and risk.

Models can be developed in parallel.


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Introduction 28

Models exist in various forms

Model template predefined, fixed structure, can be configured

Model instance objects manipulated during a project.

Model versions versions of a model instance can exist.

Multiple model instances separate instances can be developed

example: ''current'' and ''future'' organization


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Introduction 29

The Product

Instantiated models represent the important aspects of the environment and the

delivered knowledge based system.

Additional documentation information not represented in the filled model templates

(e.g. project management information)

Software

R l i k l d


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Introduction 30

Roles in knowledge-systemdevelopment

knowledge provider

knowledge engineer/analyst

knowledge system developer

knowledge user project manager

knowledge manager

N.B. many-to-many relations between roles and people


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Introduction 31

Knowledge provider/specialist

traditional expert

person with extensive experience in an applicationdomain

can provide also plan for domain familiarization where would you advise a beginner to start?

inter-provider differences are common

need to assure cooperatio


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Introduction 32

Knowledge engineer

specific kind of system analyst

should avoid becoming an "expert"

plays a liaison function between application domain

and system


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Introduction 33

Knowledge-system developer

person that implements a knowledge system on aparticular target platform

needs to have general design/implementationexpertise

needs to understand knowledge analysis but only on the use-level

role is often played by knowledge engineer


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Introduction 34

Knowledge user

Primary users interact with the prospective system

Secondary users are affected indirectly by the system

Level of skill/knowledge is important factor

May need extensive interacting facilities explanation

His/her work is often affected by the system consider attitude / active tole


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Introduction 35

Project manager

responsible for planning, scheduling and monitoringdevelopment work

liaises with client

typically medium-size projects (4-6 people) profits from structured approach


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Introduction 36

Knowledge manager

background role

monitors organizational purpose of system(s) developed in a project

knowledge assets developed/refined

initiates (follow-up) projects

should play key role in reuse

may help in setting up the right project team

Roles in kno ledge s stem


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Introduction 37

Roles in knowledge-systemdevelopment

knowledge

provider/specialist

projectmanager

knowledgesystem developer

knowledgeengineer/

analyst

knowledgemanager

knowledgeuser

KS

manages

managesuses

designs &implements

validates

elicits knowledge

from

elicitsrequirements

from

deliversanalysis models

to

defines knowledge strategyinitiates knowledge development projectsfacilitates knowledge distribution


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Introduction 38

Terminology

Domain some area of interest

banking, food industry, photocopiers, car manufacturing

Task something that needs to be done by an agent

monitor a process; create a plan; analyze deviant behavior

Agent the executor of a task in a domain

typically either a human or some software system


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Introduction 39

Terminology

Application The context provided by the combination of a task and a

domain in which this task is carried out by agents

Application domain The particular area of interest involved in an application

Application task The (top-level) task that needs to be performed in a certain

application


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Introduction 40

Terminology

knowledge system (KS) system that solves a real-life problem using knowledge

about the application domain and the application task

expert system knowledge system that solves a problem which requires a

considerable amount of expertise, when solved by humans.


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GDS

600,000 Travel Agentsuse the GDS to find and book hotels & flightsUsed by IATA approved Travel Agents world wide

40,000 Internet Distribution Systems (IDS) may use GDS *Expedia, TraveloCity etc

* IDS May pull content from GDSgiving a single point of control for multiple channels

This very powerful feature is however being depreciated asIDS opt for direct contracts with hotels

Global Exposure!!


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GDS

Started By American Airlines to let travel agents book flights (1964*)Worlds airlines joined. All system networked togetherExpanded to include hotels (1988 chains via Thisco switch)

The reservation is sent to the hotel. It is immediately available to the travel agent via the GDSand to the hotel via the GDS agent CRS (Generares and partner system (arcRes)

Travel agents search for hotels using asecure computer terminal connected toone of the 4 GDS channels- Amadeus Galileo Sabre Worldspan

Each GDS displays your hotelscurrent rates and availability

300 million reservation per month

1964* SABRE: Semi-Automated Business Resrch Environment.The larges non government database in the world


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GDS information is also available to display and book

on 1,000s of travel sites like Travelocity


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GDS NEWORK

GDS-CRS RepEg: Reserv, Unirez, Utell (Pegasus)Synix.. etc and Genares

600,000 Travel Agents use the GDSto find and book hotels & flights

40,000 Internet Distribution Systems

(IDS) may use GDS *

Interfaced to your back officemanagement/accounting andfront office reservation and web


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GDS BENEFITS

A Global Bookings Channel

Global Marketing exposing you to the global travel market

Administration

manages rates on multiple channels- integrates with backoffice, front office


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.


GENARES GDS-CRS

Combining over 35 years of experiencein the hospitality reservation technologyindustry, GENARES has developed the

first truly integrated third partycentral reservation system for

the twenty-first century

Complete open specificationand interfaces

for 3rd party integration,using XML format

The youngest and fasting growingGDS integration company

Highly recommended by existing clients


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.


GENARES RECOMENDATIONS

Hi Ian,

GenaRes is one of the best GDS providers Ive worked with within my 27 year in the industry!

In over two years now, our volume of business percentage has grown through bookings via the GDS.

I have been assigned my own support account manager and we have over the years established such

a great working relationship. She is always here for me and also when Im out of the office she is thecontact person regarding any issues with loading rates, opening/closing the system etc. Although theproperty can control basically everything own their own through the easy GenaRes system; my accountmanager has always proven to be our second hand person.

This is what I call a great support team!!

Thanks Ian and Ill be on my way to Barbados to pick up that Rum Punch!!

Call on me anytime and be well.

Best Regards,

Clayton C.ChanningReservations/Revenue Manager- flatotel.com646-756-7952

And many more


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.


Genares - full featuredCRS

Reporting

Agents Commission Tracking

IntegrationRoomMaster, IQ Ware, RSI, AutoClerk,* Opera,* Check Inn,PMS Solutions/Innkeeper,Expedia Quick Connect, ezyield

& arcRes


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Integrated with AXSES ArcRes

for fast, easy setup& management

RoomMaster, IQ Ware, RSI, Check InnExpedia Quick ConnectAutoClerk*, Opera,*PMS Solutions/Innkeeper*

* In development


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.

.


GDS and arcRes easy to use & powerful

Just a click away

Easy navigation on your arcRes home page


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.

.


arcRes GDS Setup and Load easy as 123


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.

.


arcRes - Register GDS with a Click

Registering switch and contractonline for easy access and process

Automatically generate letter and contracts with a click no paperwork!


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.

.


Load GDS rates and Content using arcRes info

We dont know of a GDSthat is as easy and ascost effective to setup

Takes all info in arcResand formats it for GDS

Allows you to save an editfor as long as you want

Saves time and improves content


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Generes GDS Marketing Key Partners

40,000 travel Sites (IDS)May pick up GDS content

Participation in worldwidetrade shows

NBTAHITEC

HEDNAAll (GDS) conferencesWTM (World Travel Mart),attendee only

ITB, attendee onlyResExpo

RFP consortia participation

Private GDS chain levelbranding programs


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GDS as Channel Manager

IDS pull from GDS (sometimes exclusively *)Some have Direct (net rates) contactsMany do both

IDS Net Rates Contract 25 - 35%Barbados Hotels pay for placement(loss of contract = loss of position)

Marketing Constraints

Being on GDS may not eliminateneed to manage direct contract(net rates) with companies like Expedia

Genares offer IDS Direct like Expedia Quick connect

40,000 travel Sites (IDS)May pick up GDS content

* priceline


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.


AFORDABLE GDS .. 5% GDS rep fee

GDS Setup $150- arcRes time saver load $ 50-Pass through $ 5.75-GDS Rep 5%- minimum monthly maintenance fee is $25.00- ODD monthly connection fee is $25.00

WebsitearcRes Bookings (i) $ 0Dynamic rates arcRes $ 75arcRes channel Management option $ 2.00

Agent Commission (TACS)per reservation to GDS $ 0.45per reservation to Perot Systems $ 0.55


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.


AFORDABLE GDS .. Just Got Better!!

Combined with arcRes for

- one of a kind marketing

- full service

- easy GDS setup

- savings


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arcRes Interactive services Increase bookings by 25%

ThemesSpecials channel

Pre-made packagesGroups managementDynamic rates & accom.CMSAffiliate marketing

Reservations Booking engine

BookingsBarbados channel

Search engine

Comparison Shopping

Dynamic packages

* Bookable Advertising!

GDS Global Distribution

750 3000 / 1500 3750


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Dynamic Bookable Advertising

rates

quotes

Full shopping cart cost and compare**** huge increase in bookability***


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.



quotes

Cost Compare of all point select.

Quotes, invoice, save, book


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.



Linked to website if advertising

- no rates

- no quotes

- no shopping

- no consistent information

NOT Bookable xx


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Dynamic Bookable Advertising everywhere!!

Soon. A bookable map for every arcres advertisier.

>>>>>>


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Advertise - Search Shop Buy . Blur >> The Perfect Storm

Each element in the search-shop-buy triumvirate is undergoing a periodof intense innovation, making each increasingly significant, yetinterdependent. In fact, searching, shopping and buying once distinctterms describing different behaviorsare blurring at a furious pace. -Philip C. Wolf, President and CEO, PhoCusWright Inc.

AXSES is there. We have already integratedadvertising with all phases of the shoppingcycle. This gives you complete flexibility inrevenue and marketing models; including anymix of transaction, commission and

subscription.

Focus direct sales facilitating distribution

Interactive advertising works! Travelers stay longer and use all options


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Saves $1000

Applies full GDS costs $300Full RH Cost $500Plus 50% on remainder


arcRes GDS PACKAGES - combinations

Saves $450

Applies full GDS costs $300Plus 50% on remainder

Non hosted - clients pay additional $250 setup and $250 pa 50% $250

Search, comparison shoppingquotes, reservations, bookingsDynamic packaging, Bookable-ads

Search, comparison shopping,quotes, reservations, bookingsBookable-ads


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knowledge engineering oxford 17 02 10 natarajan

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