Lectures on Knowledge Acquisition Artificial Intelligence CS 364

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Lectures on Knowledge Acquisition- Artificial
Intelligence (CS 364)
Khurshid Ahmad Professor of Artificial
Intelligence Centre for Knowledge Management With
additional material by Chris Handy November 2002

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Knowledge Acquisition INTRODUCTION BACKGROUND

• The important characteristics of knowledge are
  that it is experiential, descriptive,
  qualitative, largely undocumented and constantly
  changing.
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• There are certain domains where all these
  properties are found and some where there are
  only a few.
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• The lack of documentation and the fact that
  experts carry a lot of information in their
  heads, make it difficult to gain access to their
  knowledge for developing information systems in
  general and expert systems in particular.
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• Therefore, knowledge engineers have devised
  specialised techniques to extract and document
  this information in an efficient and expedient
  manner Knowledge Acquisition.

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Knowledge Acquisition INTRODUCTION BACKGROUND

• Currently knowledge bases for knowledge based
  systems are crafted by hand, this is a severe
  limitation on the rapid deployment of such
  systems.
• The automation of knowledge acquisition (from
  text) would greatly ease this problem.
• There is considerable interest in developing
  software tools which would allow the automatic
  construction of knowledge bases from textual
  information.
• This will provide the opportunity to rapidly
  build knowledge bases thus increasing, for
  example, the rate at which knowledge based
  systems can be developed and deployed

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Knowledge Acquisition INTRODUCTION BACKGROUND

• Knowledge acquisition can be regarded as a method
  by which a knowledge engineer obtains information
  from experts, text books, and other authoritative
  sources for ultimate translation into a machine
  language and knowledge base.
• The person undertaking the knowledge acquisition
  must convert the acquired knowledge into a form
  that a computer program can use.

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Knowledge Acquisition INTRODUCTION BACKGROUND
In the process of Knowledge Acquisition for an
Expert System Project, the knowledge engineer
basically performs four major tasks in
sequence  First, the engineer ensures that he or
she understands the aims and objectives of the
proposed expert system to get a feeling for the
potential scope of the project.   Second, he or
she develops a working knowledge of the problem
domain by mastering it's terminology by looking
up technical dictionaries and terminology data
bases. For this task the key sources of
knowledge are identified textbooks, papers,
technical reports, manuals, codes of practice,
and domain experts. Third, the knowledge
engineer interacts with experts via meetings or
interviews to acquire, verify and validate their
knowledge. Fourth, the knowledge engineer
produces a "paper knowledge base" a document or
group of documents which form an intermediate
stage in the translation of knowledge from source
to computer program. This comprises the
interview transcripts, the analysis of the
information they contain and a full description
of the major domain entities (e.g. tasks, rules
and objects).
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Knowledge Acquisition INTRODUCTION BACKGROUND
Knowledge engineers interview experts in a
specialist domain about how he or she solves a
given problem. Before interviewing the experts,
the knowledge engineers have to formulate their
questions, and after the interview the answers to
the questions have to be analyzed. The
knowledge engineer has to familiarize himself or
herself with the terminology of the specialist
domain he or she has to consult technical
manuals, and in some cases learned papers, to see
how the experts knowledge is applied the
knowledge engineers sometimes consults textbooks
or encyclopedic texts for understanding the
conceptual structure of the experts domain. In
many different ways the knowledge engineer
literally has to come to terms with the language
used by the expert and that used in the other
texts mentioned above. The knowledge engineer
should become conversant in the specialist
language of his or her application domain.
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Knowledge Acquisition Acquiring Problem-Solving
Knowledge
The knowledge essential for solving problems of
a given domain can be structured in a
(problem-solving) task-oriented fashion. Each
task is executed sequentially which in turn
involves the use of IF . . . THEN type constructs
- rules and rules of thumb. These rules test
and manipulate a number of abstract and physical
entities of the domain which are referred to as
domain objects.
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Knowledge Acquisition Methods and Techniques
Terminology Systematically organised collection
of terms and their elaborations, including
definitions, grammatical categories, and related
term. The system used is usually a conceptual
one. The conceptual basis is that of the
discipline and its potential application. For
example, physicists organise their subject
discipline in terms of forces, energy and mass
chemists focus on atoms and molecules biologists
organise their subject in terms of kingdoms,
families and species.
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Knowledge Acquisition Methods and Techniques
Terminology The rules in a knowledge based system
are essentially a conjunction of terms
Typical MYCIN 'rule' IF the stain of the
organism is gramneg, the morphology of the
organism is rod, the aerobicity of the
organism is aerobic THEN there is strongly
suggestive evidence (0.8) that the class of
organism is enterobacteriaceae   Typical XCON
'rule' IF The most current active context is
assigning a power supply an sbi module of
any type has been put in a cabinet the
position it occupies in the cabinet (its nexus)
is known there is space available in the
cabinet for a power supply for that nexus
there is an available power supply THEN put
the power supply in the cabinet in the available
space.   Typical PROSPECTOR 'rule' IF The
igneous rocks in the region have a fine to medium
grain size THEN they have a porphyritic texture
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Knowledge Acquisition Methods and Techniques
TerminologyProblem Solving Heuristics? Terminolo
gy of a specialist domain, and to some extent the
details of the problem-solving heuristics and
that of the meta rules, reflect the underlying
structure of the domain. This structure allows
the members of the domain community to develop
new ideas, to challenge existing wisdom, to
disseminate and to learn from each other. In
effect, the underlying structure provides a
cohesive framework for the domain community to
function as a whole. The above two statements
are of a philosophical nature and as such contain
some speculations the predication of the
structure, that helps in the evolution, revision,
propagation and application of knowledge, is one
such speculation. Some AI folk talk about
ontology as an overarching term to discuss how
the knowledge of a domain is organised. Ontology
literally means essence of being. Once this term
was used mainly in theological discussions.
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Knowledge Acquisition Methods and Techniques
Ontology AI experts, like Tom Gruber, suggest
that In the context of knowledge sharing, I use
the term ontology to mean a specification of a
conceptualization. That is, an ontology is a
description (like a formal specification of a
program) of the concepts and relationships that
can exist for an agent or a community of agents.
This definition is consistent with the usage of
ontology as set-of-concept-definitions, but more
general. And it is certainly a different sense of
the word than its use in philosophy. ( Cited from
www-ksl.stanford.edu/kst/what-is-an-ontology.html
site visited 20 November 2001)
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Knowledge Acquisition Methods and Techniques
Ontology Ontologies as a specification
mechanism A body of formally represented
knowledge is based on a conceptualization the
objects, concepts, and other entities that are
assumed to exist in some area of interest and the
relationships that hold among them (Genesereth
Nilsson, 1987) . A conceptualization is an
abstract, simplified view of the world that we
wish to represent for some purpose. Every
knowledge base, knowledge-based system, or
knowledge-level agent is committed to some
conceptualization, explicitly or implicitly.
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Knowledge Acquisition Methods and Techniques
Ontology An ontology is an explicit
specification of a conceptualization. The term is
borrowed from philosophy, where an Ontology is a
systematic account of Existence. For AI systems,
what "exists" is that which can be represented.
When the knowledge of a domain is represented in
a declarative formalism, the set of objects that
can be represented is called the universe of
discourse. This set of objects, and the
describable relationships among them, are
reflected in the representational vocabulary with
which a knowledge-based program represents
knowledge. Thus, in the context of AI, we can
describe the ontology of a program by defining a
set of representational terms. In such an
ontology, definitions associate the names of
entities in the universe of discourse (e.g.,
classes, relations, functions, or other objects)
with human-readable text describing what the
names mean, and formal axioms that constrain the
interpretation and well-formed use of these
terms. Formally, an ontology is the statement of
a logical theory. (Gruber www-ksl.stanford.edu/k
st/what-is-an-ontology.html site visited 20
November 2001 emphasis added by Khurshid Ahmad)
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Knowledge Acquisition Interviewing Techniques
for Knowledge Acquisition
The Informal or Overview Interview To
familiarise the knowledge engineer with the
domain and the particular problem which the
proposed expert system is intended to solve
  The Focused Interview Focused interviews are
similar to ordinary "chat show" conversations or
discussions where the interviewer is interested
in a topic of which the interviewee is
knowledgeable.   It is normally conducted by
following a pre-determined agenda. The
interviewee is initially prompted with the first
topic or question, but is given a great deal of
freedom of expression thereafter.  
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Knowledge Acquisition Interviewing Techniques
for Knowledge Acquisition
The Structured Interview Structured interviews
normally occur well into the knowledge
acquisition phase.   They are used when
information is required in much greater depth and
detail than the other techniques can offer and is
more interrogative than conversational.
  'Think aloud' Protocols A technique used by
cognitive psychologists to study the strategies
with which people solve problems. Case studies
are advantageous because the end results are
already known so the expert should repeat the
strategy he used for that problem when describing
his solution.  
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Knowledge Acquisition Interviewing Techniques
for Knowledge Acquisition Dos and Donts
It is essential to record and transcribe all the
(video- or audio-taped) interviews.
  Transcripts should be clearly cross-referenced
to (video- or audio-tape) recorder counter
numbers.  Include all the sketches, photocopies
or reproductions of diagrams, tables or the like,
that were referred to during the interview(s).
  Once completed a copy should be sent to the
interviewee for comments, corrections and
criticism. There is always the possibility of
misunderstanding by the knowledge engineer when
interpreting a statement or explanation.   By
involving the expert in validating his or her own
transcript it reduces the chance of erroneous
information appearing in the prototype's
knowledge base.
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Knowledge Acquisition Tasks performed by a
knowledge engineer
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Background  Project PLAIM (Platform Lifetime
Assessment through Analysis, Inspection and
Maintenance) was sponsored by the European Union
during 1988-89. The project had two major
objectives first to collate, analyze and archive
the inspection and maintenance related data.
And, the second aim is to establish a computer
program which will (a) allow access, indeed
guide the user to the appropriate data (or data
files)   (b) provide an 'intelligent'
interface to mathematical models,
industry-standard simulation programs and
empirical equations (this intelligence will help
a (novice) end-user to run simulation programs
and interpret output provided by the programs)
and   (c) acquire, formalise and disseminate the
experiential and hitherto undocumented knowledge
of inspecting and maintaining off-shore
structures.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Interviews   A total of three knowledge
elicitation interviews were conducted lasting
over 5 hours and covering a broad range of topics
relevant to the target problem   The first
interview provided the overview The second being
much more focused on domain description and
terminology. The third interview was the only
formally conducted, structured interview.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Interviews   Regular prototype revision meetings
were conducted in a similar interrogative style
inspired by a demonstration of the prototype and
review of the current knowledge base.   All
but one of the interviews were recorded using a
video-cassette recorder all were transcribed
and, where considered useful, the transcripts
were sent to or discussed with the interviewee.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Interviews
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Overview Interview   As indicated above, the
overview interview requires the preparation of a
well targeted set of questions. The interviewee,
the PLAIM project manager, was video taped and a
transcript of his interview was produced. The
interview began with a discussion of a 'flow
chart' for conducting fatigue analysis of
offshore structures.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Overview Interview   The interviewer, who already
had access to a variety of contract documents
related to PLAIM, asked the expert to explain the
'flow chart'. This led to the following set of
well focused questions
Please outline algorithms, data input and output,
data requirements What sort of knowledge and
expertise is expected to be included in this
prototype? Please give your view on judgments on
accuracy and calibration with real data? How do
you tell from residual strength and reliability
index the lifetime of the structure or cracked
joint? i.e. how long before the crack causes
failure?  In relation to the flow diagram, what
is current practice and who currently carries out
each of the jobs? What is the expertise involved?
Who would be the target user of the
prototype? What changes in data, apart from the
loading conditions, should the user be
interrogated or the system should look
for?  Please suggest further information sources.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Overview Interview   The result of the overview
interview led to the identification of the broad
scope of the project and in cataloguing important
technical documentation as textual knowledge
sources. The preparation of the questionnaire
for the interview helped the knowledge engineer
to learn much about the expert's impression of
the problem and his understanding of how an
expert system could be applied. Some key phrases
of the domain terminology were also introduced
and explained.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Overview Interview   A number of knowledge
sources were identified by the domain experts
ranging from research papers in learned journals
to textbooks and repair and maintenance manual.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Focused Interview This purpose of this interview
was to cover two broad topics. Firstly, to
describe a typical oil production platform and
secondly to outline fatigue damage design,
analysis and repair practices. The help of a
second domain expert, who has hands-on experience
of designing such structures, was enlisted His
reply comprised the following topics (The
numbers on the right are video-recorder
counters  000 Major Components of a Typical
Platform (Example 1) 063 Example 2 - A Barge
Launched Jacket 125 Fatigue Problem
Areas 140 Pile Sleeves 157 Nodes 170 Importanc
e of Various Members in a Jacket 222 Scour
problems 254 Anodes and Corrosion
Protection 273 Defects 313 Fatigue Analysis
Procedure and Calculations 357 Wave Data
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Focused Interview- Fragment of the Tape 000
Major components of a Typical rig (Example 1) The
diagram shows the topside, consisting of the
cellar deck to support the drilling rig,
accommodation module, helideck etc. Also shown
are the flare boom and other crane booms. The
jacket supports the topside fixing it securely to
the sea-bed above the level of the highest waves
likely to be encountered in the North Sea. Piles
are driven through guides in the legs of the
jacket into the bed rock to ensure the rig
position is solid. As the jacket structure is a
group of frames made up of tubular steel sections
and linked together by other frames, a method of
identifying individual members and nodes at which
groups of members coincide is required. The
convention used on engineering drawings to
identify the frame structure in plan view at each
level or staging is shown below. This particular
jacket was lifted into place using a crane.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Focused Interview- Fragment of the Tape 015
The isometric view (below) of the same jacket
shows in more detail aspects of the frame
structure the type of loading experienced and
typical trouble spots. The increasing diameter
of the leg is so that it is strong enough to be
able to take the increasing axial load at the
lower levels. When a wave hits the platform it
causes an overturning moment which in turn causes
an axial load in the leg. This is resisted by
the piles, but in this example the eccentricity
of the load due to the leg shape causes flexure
in the short stubby diagonal braces and causes
fatigue problems in their corresponding node
joints. Other crossed-diagonal members also
experience fatigue due to this sort of flexure
but not to the same degree.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Focused Interview- Fragment of the Tape Domain
Objects
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Focused Interview- Fragment of the Tape Domain
Objects

• The domain objects shown above encompass
• Names of entities
• Classes of entities
• Functions that return values of the attributes of
  the entities
• Predicates that show relationship between
  entities.

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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Focused Interview- Fragment of the Tape Rules
from the tape fragments Counter 000
rule 1 if jacket is barge launched then jacket
will have extra structural members included
purely for transportation and launching which
become redundant once it is placed on the sea
bed. rule 2 if a wave strikes the
jacket then the diagonal members will take the
load/shear force. rule 3 if a jacket has sloping
legs then any crossed diagonal members at the
lowest level will flex and cause fatigue in
their corresponding node joints.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Focused Interview- Fragment of the Tape Rules
and explanations from the tape fragments Counter
000
rule 1 if jacket is barge launched then jacket
will have extra structural members included
purely for transportation and launching which
become redundant once it is placed on the sea
bed. because it is a big structure and two
different types of loading conditions need to
be designed for if it is not going to fail under
either. rule 2 if a wave strikes the
jacket then the diagonal members will take the
load/shear force. because the wave causes an
overturning moment which will effectively
tension one side of the jacket and compress the
other side. In resisting this movement the
diagonals take much of the load.
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Knowledge Acquisition PLAIM A Case Study in
Interview-based KA
Focused Interview- Correction to the tape
transcript
Corrections to the transcript  The interview
transcript was sent to the expert for comments
and criticism and was duly returned with
corrections. It is not easy to classify the
comments, except that the expert imposed
constraints on his statements or expanded on
others. Some examples below are presented to
highlight the point we have just made. The
amendments are shown in italics   000 Major
components of a Typical rig (Example 1) The
diagram shows the topsides, consisting of the
cellar deck to support the drilling rig,
accommodation module, helideck etc. Also shown
is the flare boom and other crane booms. The
jacket supports the topsides fixing it securely
to the sea-bed above the level of the highest
waves likely to be encountered in the North Sea
at the site. Piles are driven through guides
attached to the legs of the jacket into the sea
be to ensure the rig position is
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Knowledge Acquisition Methods and Techniques

• A knowledge engineer must be
•  
• Familiar with the applications domain, its
  terminology and conceptual structure (or
  ontology)
• Able to map the domain knowledge onto a
  representation schema
• Map the representation onto a suitable inference
  strategy.