KM-Techniques.ppt

8/22/2019 KM-Techniques.ppt

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2001 Franz J. Kurfess Knowledge Management Techniques 1

CPE/CSC 580:

Knowledge Management

Dr. Franz J. Kurfess

Computer Science DepartmentCal Poly


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Course Overview

IntroductionKnowledge Processing

Knowledge Acquisition,

Representation and

Manipulation

Knowledge Organization Classification, Categorization

Ontologies, Taxonomies,

Thesauri

Knowledge Retrieval Information Retrieval

Knowledge Navigation

Knowledge Presentation

Knowledge Visualization

Knowledge Exchange Knowledge Capture, Transfer,

and Distribution

Usage of Knowledge

Access Patterns, User

Feedback

Knowledge Management

Techniques

Topic Maps, Agents

Knowledge ManagementTools

Knowledge Management in

Organizations


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Overview Knowledge Management

Techniques

Motivation

Objectives

Evaluation Criteria

Chapter Introduction Review of relevant concepts

Overview new topics

Terminology

Topic 1 Subtopic 1.1

Subtopic 1.2

Topic 2

Subtopic 2.1

Subtopic 2.2

Topic 3 Subtopic 3.1

Subtopic 3.2

Important Concepts and

Terms

Chapter Summary


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Logistics

Introductions

Course Materials

textbook

handoutsWeb page

CourseInfo/Blackboard System and Alternatives

Term Project

Lab and Homework Assignments

Exams

Grading


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Knowledge Repositories

[KPMG 1998]
http://localhost/var/www/apps/conversion/tmp/scratch_7/Knowledge-Exchange.ppthttp://localhost/var/www/apps/conversion/tmp/scratch_7/Knowledge-Exchange.ppt


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KM Infrastructure


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KM Initiatives



Pre-Test



Motivation



Objectives



Corporate Memory (CM)

definition attempts

purpose

concepts

implementation



Definition Attempts Corporate

Memoryexplicit, disembodied, persistent representation of

knowledge and information in an organization [Van

Heijst, van der Spek and Kruizinga 1996]

may include knowledge on products, production

processes, clients, marketing strategies, plans, strategic

goals, etc.

the collective data and knowledge resources of a

company [Nagendra Prasad and Plaza 1996]may include project experiences, problem-solving

expertise, design rationale, etc.

[Dieng et al. 1999]



Purpose Corporate Memory

capitalization of knowledge

integration of resources and know-how

cooperation through effective communication and

active documentationthe right knowledge to the right person at the right

time and at the right level

[Dieng et al. 1999]



Links in the Knowledge Chain

list existing knowledge

determine required knowledge

develop new knowledge

allocate new and existing knowledgeapply knowledge

maintain knowledge

dispose of knowledge

[Dieng et al. 1999]



Corporate Memory Management

detection of needs

construction of the corporate memory

diffusion of the corporate memory

use of the corporate memoryevaluation

maintenance and evolution

[Dieng et al. 1999]



Corporate Memory Management

Overview

[Dieng et al. 1999]



Multidisciplinary Perspective on CM

technological (computer science, informationtechnology)

concentrate on technical and implementation aspects

may neglect requirements and constraints of systems in

practical use

organizational (CKO)

emphasize the role of CM in an organization

may overlook technological problems, or underestimateefforts needed for implementation

[Dieng et al. 1999]



Corporate Memory Techniques

[Dieng et al. 1999]



Corporate Memory Example

[Dieng et al. 1999]


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Motivations for Establishing a CM

avoid knowledge loss departure, retirement, change of roles of employees

exploit past experience

cumulative technical know-how

successful and failed projects

utilize collective knowledge for strategic purposes

detection of new opportunities

reaction to changes

improve knowledge exchange and communication establish venues for sharing information

improve learning

integrate knowledge from different areas

cross-disciplinary knowledge exchange[Dieng et al. 1999]


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Knowledge in Organizationsexplicit knowledge

specific know-how to design, build, sell and support

products and services

tacit knowledge

individual and collective skills enabling the organization toact, adapt, and evolve

tangible knowledge components

data, procedures, plans, models, algorithms, documents of

analysis and synthesisintangible knowledge components

abilities, professional skills, private knowledge,

organizational culture, history of the organization, contexts

of decisions, etc.[Dieng et al. 1999]


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Types of Corporate Memories

technical memory know-how of the employees about technical aspects

organizational memory

knowledge about the internal structure of an organizationproject memories

lessons and experiences from past projects

individual memories

status, know-how, activities, relationships of individual

employees

internal vs. external memory

indicates the source of relevant knowledge and information[Dieng et al. 1999]


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CM Needs

organization is also a knowledge production unit not necessarily as primary purpose

depends on size, type, and organizational scheme of

the organization e.g. distributed network of consultants

needs of individual users vs. organizational needs

detecting the right needs can be difficult

target users, domains, tasks, situations, knowledge

[Dieng et al. 1999]


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Determination of CM Needs

stakeholder-centered influenced by the members of the community of people

affected by or invested in the system

requirements analysis

early involvement of stakeholders is critical and feasible

most stakeholders are internal to the organization, and many are

motivated

most solutions are adaptations or evolutions of

previous systems

CSCW, KBMS, MIS, ...

[Dieng et al. 1999]


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CM Construction

sources

non-computational CM

document-based CM

knowledge-based CMcase-based CM

distributed CM

project-centered CMcombinations of several techniques

[Dieng et al. 1999]


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Sources

human sources domain experts, experienced specialists, people with

organizational memories

physical documents

printed documents, notes, design artifacts, products, tools,

etc.

digital documents

reports, technical documentation, design artifacts, email,case libraries, dictionaries, sketches, etc.

[Dieng et al. 1999]


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Non-computational CM

establishment of paper-based knowledge repository existing documents

generation of new documents

synthesis of knowledge not explicit in reports, technical

documentation, etc.

improve strategies and structural aspects of the organization

systematic generation of knowledge in an

organization

may be the predecessor to a digital CM

[Dieng et al. 1999]


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Document-based CM

comprises all existing documents in an organizationmay be in paper-based or digital form

organizes the collection in a systematic way

indexing interface to manage documents

preparation, storage, retrieval, processing, evaluation, distribution

[Dieng et al. 1999]


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Knowledge-based CM

based on the elicitation and explicit modeling ofknowledge from experts

may use a formal knowledge representation

framework this is often quite expensive

serves as an assistant to human knowledge

workers

different from traditional expert systems their goal is the automation of a particular task

[Dieng et al. 1999]


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Case-based CM

utilizes case-based reasoning

past experiences are collected in a (semi-)formal

representation mechanism

allows the comparison of cases the assumption is that new problems can often be solved

by looking up solutions to previous problems

helps with the concentration of expertise around

specific casescontinuous evolution of the CM through the

continuous addition of new cases

[Dieng et al. 1999]


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Distributed CM

emphasis on collaboration and knowledge-sharingacross traditional boundaries

geographically distributed persons/groups

structurally separated entities

common tasks, domains

essential for virtual organizations

teams or people collaborate on-line

[Dieng et al. 1999]


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Project-centered CM

captures the relevant knowledge accumulated whileworking on a project

discussions, arguments, decisions, compromises, etc.

important aspects

represent and reconcile perspectives of differentstakeholders

changes of priorities in the project

communication of decision rationales

recovery of insights and solutions from past scenarios

re-inventing the wheel

example

issue-based information system (IBIS) [Rittel 1972][Dieng et al. 1999]


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Combinations of Several Techniques

informal and formal knowledge representationmethods

combination of paper-based and digital documents

semi-automatic extraction of knowledgecollaborative construction of community knowledge

integration of existing components

libraries, data bases, case bases, document collections,

multi-media collections, etc.

[Dieng et al. 1999]


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Diffusion and Use of CM

diffusion modes knowledge attic

archive that can be consulted when needed

collection and diffusion are passive

knowledge sponge active collection, passive diffusion

knowledge publisher

relevant elements are distributed to users

passive collection, active distribution

knowledge pump

specific roles or methods for collection of relevant knowledge

active collection and active diffusion

[Dieng et al. 1999]


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Diffusion via Intranet/Internet

frequently centered around Web servers

has some conceptual and technical limitations, but

substantial benefits

confidentiality, security, reliability, distraction, etc.

[Dieng et al. 1999]

K l d d I f ti


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Knowledge and Information

Retrievaltraditional index-based techniques are integrated in

most approaches to CM

enhancements through advanced techniques

ontologies collaborative filtering

intelligent agents


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Evaluation

financial perspective improve the bottom-line of the organization

may be difficult to measure

organizational perspectivework environment

employee satisfaction

technical perspective

transfer of know-how

some effects may not be direct consequences of the

CM, but side-effects of its introduction or use

[Dieng et al. 1999]


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Maintenance and Evolution

should be based on the evaluation of the currentsituation

addition of new knowledge

removal or modification of obsolete knowledgecoherence problems

scalability

user acceptanceshould become a continuous activity

[Dieng et al. 1999]


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Examples of CM Methods

CYGMAREX

MKSM

KAMM

[Dieng et al. 1999]


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CYGMA

Cycle de Vie et Gestion des Mtiers et desApplications, KADE-TEX

construction of a professional memory in

manufacturing

relies on six categories of industrial knowledge

singular knowledge

terminological knowledge (dictionary)

structural knowledge (ontology, factual knowledge base)

behavioral knowledge

strategic knowledge

operational knowledge

[Dieng et al. 1999]


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REX

needs analysis and identificationconstruction of elementary pieces of experiences

construction of a computer-based representation

implementation through a software system

[Dieng et al. 1999]


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MKSM

Method for Knowledge System Managementsystemic-based decision support method

views knowledge assets as a complex system

models this complex system through differentperspectives

syntactical, semantic, pragmatic

different components

information (data processing)

signification (task modelling)

context (activity modelling)

[Dieng et al. 1999]


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KAMM

[Knowledge Associates 2000]


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KAMM Architecture

[Knowledge Associates 2000]


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Knowledge Technology Framework

identifies key KM activities and relatedknowledge[oriented techniques and tools

personalization

codificationdiscovery

creation/innovation

capture/monitor

[Milton et al. 1999]


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Knowledge Technology

(Key: P"Person, K1"Knowledge 1echnology, I1"Information 1echnology)


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Personalization

sharing knowledge through person-to-personcontacts

tools for more effective communication

email, message boards, chatrooms, personal ontologies



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Codification

capturing existing knowledge and placing it inrepositories

tools and techniques for knowledge representation

generic models

rules, frames, case-based reasoning, ...

specialized techniques

task- or domain-specific



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Discovery

searching and retrieving knowledge from repositoriesand data bases

tools and techniques from information retrieval,

knowledge-based systems, natural language

processing

search engines, ontologies



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Creation/innovation

generation of new knowledgetools and techniques from cognitive science,

psychology

brainstorming support, creativity assistance

mainly a human endeavor



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Capture/Monitor

capturing knowledge as people work on their normaltask

tools and techniques from Human-Computer

Interaction, AI

audit trails, case collections



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KM Framework

[Macintosh et al. 1999]


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KM Processes

[Macintosh et al. 1999]


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PROMOTE Architecture

[Karagiannis & Telesko, 2000]


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PROMOTE

Framework

[Karagiannis & Telesko, 2000]


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Organizational Memory Context

[Abecker et al. 1998b]


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Context-

SensitiveKnowledge

Supply



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Integration of Ontologies


K l d T k S t


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Knowledge Task Support


Related Research Areas


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Related Research Areas



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Developing a Knowledge

Management Technology

An Encompassing View on the Projects of

theKnowledge Management Group at DFKI

KaiserslauternMichael Sintek, Andreas Abecker,

Ansgar BernardiGerman Research Center for Artificial

Intelligence

Kaiserslautern, Germany[Abecker et al. 1998b]


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Overview

requirements and approaches to support KM infrastructuresfor organizations; related research fields

KnowMore active knowledge supply finished

Know-Net collaboration ongoing

FRODO distribution, framework current

MOTIVE 3D access planned

summary: we propose a rich, modular KM middleware as asolid basis for engineering intranet-based KM solutions

Development of Knowledge

Management technology of theKnowledge Management Group at

DFKI Kaiserslautern


Knowledge is an Important


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Knowledge is an Important

Productivity Factor for Organizations

besides labor, capital, and land, knowledge has

been recognized as an important productivity factor

knowledge is stored in individual brains or implicitly

encoded and hidden in organizational processes,

documents, services, and systemsKM is concerned with discovery, acquisition, creation,dissemination, and utilization of knowledge.


rgan za ons ave er ous


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gProblems in Managing Their

Corporate Knowledge

Various fields of computer science tackle some of theseknowledge problems.

KnowledgeProblems

Documentation

Availability

Awareness

Distribution

Resources

Multiple Formats

Multiple Views

Accessibility Discovery

Acquisition



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Resarch Fields Related to KM

Groupware, Workflow, CSCW collaboration of individuals and departments

Document management, retrieval, and

filtering systems

most of the available abstract, strategic

knowledge written down in text-based documents

often advertised as KM solutions

Artificial Intelligence formal ontologies

data mining

case bases

expert systems

We strive for a new quality of knowledge systems by

integrating allthese areas.


now ore now e gei
http://localhost/var/www/apps/conversion/tmp/scratch_7/Knowledge-Exchange.ppthttp://localhost/var/www/apps/conversion/tmp/scratch_7/Knowledge-Exchange.ppthttp://localhost/var/www/apps/conversion/tmp/scratch_7/Knowledge-Exchange.ppt


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gManagement for Learning

Organizationsbasic research project funded by German

government

central idea: access to multiple

heterogeneous knowledge sources

enabled through comprehensive knowledge

description using several formal ontologies

(information, domain, enterprise ontology)

In KnowMore, knowledge can be viewed as informationlinked into the application context.


h hi


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The KnowMore System Architecture


now- e now e gei h


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gManagement with Intranet

Technologiesfunded by the European Commission within

the IT for learning and training industry

program

integrate groupware functionalities with AImethods enabling the handling of knowledge

objects

based on Knowledger suite (Lotus Notesapplication from Knowledge Associates) and

intelligent agents (DFKI)

intranet- and agent-based knowledge

platform:

In addition to a KnowMore-like knowledge platform,

collaborative aspects play an important role.


K N C ll b i A


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Know-Net: Collaborative Aspects

collaborative tools supporting communities of

practice at the team level to facilitate the

creation of shared memories and

interpretative context

real-time group discussions/meetings

project-based bulletin boards and forums

on-line topical conferences with threading features

and interactive expertise databases


The Know-Net Intranet- and Agent-


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The Know Net Intranet and Agent

Based System Architecture


ca a eF k f E l i G h


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Framework for Evolutionary Growth

(future work)

basic research project funded by Germangovernment, successor project of KnowMore

KnowMore: global set of ontologies,

centralized inference

FRODO: conjointly use knowledge from

several independent knowledge sources

legacy databases

independently introduced partial OMs based onspecific ontologies

external knowledge sources (with own ontologies)

ontology mapping problem

communicating and

cooperating servicesWe propose a rich, modular KM middleware as a solidbasis for engineering intranet-based KM solutions.


The FRODO KM Middleware Will


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The FRODO KM Middleware Will

Exploit Various Notions of Agents

digital reference and acquisition librarians

know their respective knowledge source and

organization principles

know how to effectively access, search, maintainthe knowledge

wrappers, mediators, ontologists, knowledge

brokers

add intelligent interfaces to legacy systems

make sources accessible to higher-level inferences

document analysis and information extraction

specialists [Abecker et al. 1998b]

A Sample Instantiation of the


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p

FRODO OM Framework


Users Motivation for Accessing


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g

Online Learning & Training

Resources (planned)will be submitted to the EU 5th frameworkonline front-end to electronic learning and

training (L&T) systems

addresses users motivation; important drivingfactor is social interaction

MOTIVE proposes an environment that wrapsL&T tools and content together with peoplesinteractions

virtual representation of the L&T environment:

workspace with 3D representation of the[Abecker et al. 1998b]

MOTIVE Adds Access to L&T OMs
http://localhost/var/www/apps/conversion/tmp/scratch_7/Knowledge-Exchange.ppthttp://localhost/var/www/apps/conversion/tmp/scratch_7/Knowledge-Exchange.ppthttp://localhost/var/www/apps/conversion/tmp/scratch_7/Knowledge-Exchange.ppt


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Through 3D Knowledge Portal

the L&T contents is accompanied by a

KnowMore/FRODO-like knowledge meta-level

based upon various ontologies

XML as upcoming standard will be used for

this knowledge representation task

a 3D knowledge portal wraps these ontologies

to provide a highly motivating access to the

L&T resources

thus, the MOTIVE 3D knowledge access can

be viewed as an additional but hi hl user-

In general, 3D spaces can be used to replace legacyinformation retrieval, knowledge acquisition, andworkflow frontends of OM systems.


S


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Summary

In our view, KM technology is a

combination of:

distributed, heterogeneous knowledgesources

various formal ontologies (information,

domain, enterprise)

knowledge meta-descriptions

informal-formal transitions[Abecker et al. 1998b]

R f [K 00]


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Reference [Kearns 00]

[Dieng et al. 1999]

R f [S ill 01]


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Reference [Sommerville 01]

[Sommerville 01]

[Sommerville 01]

P t T t


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Post-Test

R f


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References

[Abecker et al. 1998] Andreas Abecker, Ansgar Bernardi, Knut Hinkelmann, Otto Khn, Michael Sintek.

Techniques for Organizational Memory Systems. Technical ReportD-98-02, DeutschesForschungszentrum fr Knstliche Intelligenz (DFKI), 1998.

[Abecker et al. 1998b] Andreas Abecker, Ansgar Bernardi, Knut Hinkelmann, Otto Khn, Michael Sintek.

Toward a Technology for Organizational Memories. IEEE Intelligent Systems, vol. 13, no.3, pp. 40-48,

1998.

[Dieng et al. 1999] Rose Dieng, Olivier Corby, Alain Giboin and Myriam Ribiere, Methods and Tools for

Corporate Memory. Int. J. Human-Computer Studies, no. 51, pp. 567-598, 1999.

[Karagiannis & Telesko, 2000] Dimitris Karagiannis and Rdiger Telesko. The EU-Project PROMOTE: A

Process-oriented Approach forKnowledge Management. Proc. of the Third Int. Conf. on Practical Aspects

of Knowledge Management (PAKM2000) Basel, Switzerland, 30-31 Oct. 2000, (U. Reimer, ed.).

[KPMG 1998] KPMG Management Consulting Knowledge Management Research Report 1998.

[Macintosh et al 1999] Ann Macintosh, Ian Filby, and John Kingston. Knowledge Management Techniques

- Teaching and Dissemination Concepts. Int. J. Human-Computer Studies, no. 51, pp. 549-566, 1999.

[Milton et al. 1999] Nick Milton, Nigel Shadbolt, Hugh Cottam, and Mark Hammersly. Towards a

Knowledge Technology for Knowledge Management. Int. J. Human-Computer Studies, no. 51, pp. 615-

641, 1999

[Sintek et al. 1998] Michael Sintek, Andreas Abecker, Ansgar Bernardi. Developong a Knowledge

Management Technology. Presentation at WET ICE KMN 99, Deutsches Forschungszentrum fr

Knstliche Intelligenz (DFKI), 1999; www.dfki.uni-kl.de/~simtek/.

I t t C t d T
http://www.dfki.uni-kl.de/~simtek/http://www.dfki.uni-kl.de/~simtek/http://www.dfki.uni-kl.de/~simtek/http://www.dfki.uni-kl.de/~simtek/


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Important Concepts and Terms natural language processing

neural network predicate logic

propositional logic

rational agent

rationality

Turing test

agent

automated reasoning belief network

cognitive science

computer science

hidden Markov model

intelligence

knowledge representation

linguistics

Lisp

logic machine learning

microworlds

Summary Chapter Topic


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Summary Chapter-Topic


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KM-Techniques.ppt