codification table
TRANSCRIPT
6: Knowledge Codification
Virach Sornlertlamvanich
1 Knowledge Management System, Virach Sornlertlamvanich ([email protected])
Review of Lecture 5
On-site Observation (Action Protocol)
Brainstorming (Conventional & Electronic)
Consensus Decision Making
2 Knowledge Management System, Virach Sornlertlamvanich ([email protected])
Review of Lecture 5
Repertory Grid
Construct T1 T2 T3
1 Inexperience 3 3 1 2 Appearance 3 2 1
… … … … 5 Late 2 3 2
Delphi Method
Nominal Group Technique 3 Knowledge Management System, Virach Sornlertlamvanich ([email protected])
Review of Lecture 5
helper of
Beard
White horse
Birthday
At chimneys On roofs
Spain climbs
listens
lives in
brings gives not same as
has
has
lives in
rides
SAINT NICOLAS BLACK
PETER
Presents Santa Clause Blackboarding
Concept Map
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This Week’s Objectives What Does Knowledge Codification Involve? Benefits of Knowledge Codification Pre Knowledge Codification Questions Tools and Procedures The Role of Planning
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Knowledge Codification Modes of Knowledge Conversion Codifying Knowledge Codification Tools/Procedures
Knowledge Maps Decision Table Decision Tree Frames Production Rules Case-Based Reasoning Knowledge-Based Agents
Knowledge Developer's Skill Set Knowledge Requirements Skills Requirements
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Knowledge Codification in the KM System Life Cycle
KNOWLEDGE CAPTURE (Creation)
KNOWLEDGE TRANSFER
KNOWLEDGE SHARING
TESTING AND DEPLOYMENT
KNOWLEDGE CODIFICATION
KNOWLEDGE BASE
DATABASES
Decision tables, Decision trees, frames maps, rules
Capture Tools Programs, books, articles, experts
Intelligence gathering
GOAL
Explicit Knowledge
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What Does Knowledge Codification Involve?
Converting “tacit knowledge” into “explicit usable form” Converting “undocumented” information into
“documented” information Representing and organizing knowledge before it is
accessed It is making institutional knowledge visible, accessible, and
usable for decision making
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Benefits of Knowledge Codification Instruction/training—promoting training of junior personnel
based on captured knowledge of senior employees Prediction—inferring the likely outcome of a given situation
and flashing a proper warning or suggestion for corrective action
Diagnosis—addressing identifiable symptoms of specific causal factors
Planning/scheduling—mapping out an entire course of action before any steps are taken
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The knowledge developer should note the following points before initiating knowledge codification:
Recorded knowledge is often difficult to access (because it is either fragmented or poorly organized).
Diffusion of new knowledge is too slow. Knowledge is nor shared, but hoarded (this can involve
political implications). Often knowledge is not found in the proper form. Often knowledge is not available at the correct time when it is
needed. Often knowledge is not present in the proper location where
it should be present. Often the knowledge is found to be incomplete.
10 Knowledge Management System, Virach Sornlertlamvanich ([email protected])
Pre-KC Questions What organizational goals will the
codified knowledge serve? Why is the knowledge useful? How would one codify knowledge?
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Modes of Knowledge Conversion Conversion from tacit to tacit knowledge produces
socialization where knowledge developer looks for experience in case of knowledge capture.
Conversion from tacit to explicit knowledge involves externalizing, explaining or clarifying tacit knowledge via analogies, models, or metaphors.
Conversion from explicit to tacit knowledge involves internalizing (or fitting explicit knowledge to tacit knowledge.
Conversion from explicit to explicit knowledge involves combining, categorizing, reorganizing or sorting different bodies of explicit knowledge to lead to new knowledge.
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Nonaka's Model of Knowledge Creation & Transformation (SECI Model)
Codifying Knowledge An organization must focus on the following before
codification: What organizational goals will the codified knowledge serve? What knowledge exists in the organization that can address these
goals? How useful is the existing knowledge for codification? How would someone codify knowledge?
Codifying tacit knowledge (in its entirety) in a knowledge base or repository is often difficult because it is usually developed and internalized in the minds of the human experts over a long period of time.
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Some Codification Tools Knowledge Map Decision Table Decision Tree Frames Production Rules Case-based Reasoning Knowledge-Based Agents
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Knowledge Map Visual representation of knowledge, not a repository Identify strengths to exploit and missing knowledge gaps to fill Can be applied in Knowledge Capture A straightforward directory that points people to where they
can find certain expertise Capture both explicit and tacit knowledge in documents and in
experts’ heads
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Knowledge Map (Relationships among Departments)
www.nwlnk.com ©Copyright 2004
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Knowledge Map A popular knowledge map used in human resources is a skills planner in which employees are matched to jobs. Steps to build the map:
A structure of the knowledge requirements should be developed. Knowledge required of specific jobs must be defined. You should rate employee performance by knowledge competency. You should link the knowledge map to some training program for career development and job advancement.
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The Building Cycle Once where knowledge resides is
known, simply point to it and add instructions on how to get there
An intranet is a common medium for publishing knowledge maps
Main criteria: clarity of purpose, ease of use, accuracy and currency of content
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Decision Trees Composed of nodes representing goals and links representing
decisions or outcomes All nodes except the root node are instances of the primary
goal. (See next figure) Often a step before actual codification Ability to verify logic graphically in problems involving complex
situations that result in a limited number of actions
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Discount Policy (A Decision Tree)
Discount Policy
Customer is library or individual
Less than 6 copies
6-19 copies
20-49 copies
50 or more copies
Discount is NIL
Discount is 5%
Discount is 10%
Discount is 15%
Customer is bookstore
Less than 6 copies
Discount is NIL
6 or more copies
Discount is 25%
Discount ?
Discount ?
Discount ?
Discount ?
Discount ?
Discount ?
Order size ?
Order size ?
Bookstore
Not a bookstore
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Decision Tables More like a spreadsheet—divided into a list of conditions and
their respective values and a list of conclusions Conditions are matched against conclusions (See next table) It is another technique used for knowledge codification. It consists of some conditions, rules, and actions.
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Discount Policy (A Decision Table)
Condition Stub Condition Entry 1 2 3 4 5 6
Customer is bookstore Order size > 6 copies Customer is librarian/individual IF Order size 50 copies or more (condition) Order size 20-49 copies Order size 6-19 copies
Y Y N N N N Y N N N N N Y Y Y Y Y N N N Y N N Y N
Allow 25% discount Allow 15% discount Allow 10% discount THEN Allow 5% discount (action) Allow no discount
X X X X X X
Action Stub Action Entry
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Decision Table (an example) A phonecard company sends out monthly invoices to
permanent customers and gives them discount if payments are made within two weeks. Their discounting policy is as follows:
“If the amount of the order of phonecards is greater than $35, subtract 5% of the order; if the amount is greater than or equal to $20 and less than or equal to $35, subtract a 4% discount; if the amount is less than $20, do not apply any discount.”
We shall develop a decision table for their discounting decisions, where the condition alternatives are `Yes' and `No'.
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Decision Table (an example)
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Decision Table (an example) It is also a knowledge codification technique. A decision tree is usually a hierarchically arranged semantic
network.
A decision tree for the phonecard company discounting policy (as discussed above) is shown next.
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Decision Table (an example)
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Frames Represent knowledge about a particular idea in a data
structure Handle a combination of declarative and operational
knowledge, which make it easier to understand the problem domain
Key elements of frames: Slot: A specific object being described/an attribute of an entity. Facet: The value of an object/slot.
When all the slots are filled with values, the frame is considered instantiated
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An Automobile Example Generic AUTOMOBILE Frame
Specialization: VEHICLE
Generalization: (STATION-WAGON, COUPE, SEDAN)
.
.
. Year: Range: (1940 – 1990) If-Changed: (ERROR: Value cannot be modified)
.
.
.
Generic COUPE Frame
Specialization: AUTOMOBILE
Generalization: (SMITH’S AUTOMOBILE, HANSON’S AUTOMOBILE)
Doors: 2
SMITH’S AUTOMOBILE Frame
Specialization: COUPE
.
.
. Year: 1990
Doors: ( )
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Production Rules Tacit knowledge codification in the form of premise-
action pairs Rules are conditional statement that specify an action to
be taken if a certain condition is true The form is IF… THEN, or IF…THEN…ELSE Example: IF income is “average” and pay_history is “good” THEN recommendation is “approve loan”
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Case-Based Reasoning (CBR) CBR is reasoning from relevant past cases in a manner
similar to humans’ use of past experiences to arrive at conclusions
Goal is to bring up the most similar historical cases that match the current case
More time savings than rule-based systems Requires rigorous initial planning of all possible variables
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Generic CBR Process
User Partial Description of a
New Problem Specify Attributes of Problem
Match Attributes to Those in Case
Base
User
Case Base
Submits
Similar Cases
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Role of Planning (Earlier Steps) Breaking the KM system into modules Looking at partial solutions Linking partial solutions via rules and procedures to arrive
at the final solution Making rules easier to review and understand
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Role of Planning (Latter Steps) Deciding on the programming language Selecting the right software package Developing user interface and consultation facilities Arranging for the verification and validation of the system
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Knowledge-Based Agents An intelligent agent is a program code which is capable of
performing autonomous action in a timely fashion. They can exhibit goal directed behaviour by taking initiative. They can be programmed to interact with other agents or
humans by using some agent communication language. In terms of knowledge-based systems, an agent can be
programmed to learn from the user behaviour and deduce future behaviour for assisting the user.
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Knowledge Developer's Skill Set Knowledge Requirements
Computing technology and operating systems. Knowledge repositories and data mining. Domain specific knowledge. Cognitive psychology.
Skills Requirements Interpersonal Communication. Ability to articulate the project's rationale. Rapid Prototyping skills. Attributes related to personality. Job roles.
35 Knowledge Management System, Virach Sornlertlamvanich ([email protected])