ptit481 km unit 1

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    Course Deliveries

    Discussions

    Inputs

    Clarifications Check What I Know (CWIK)

    Clarifications

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    UNIT 1 OBJECTIVES

    Understand key terms

    Create a platform for KM

    Importance of KM Emergence of KM

    Objectives of KM

    KM Domain &U

    ses Knowledge Economy

    Knowledge Engineering & Knowledge Ontology.

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    Introduction to Knowledge

    ManagementKey terms

    Information

    Tangible raw data. Can be copied.

    Knowledge

    Intangible. Requires learning & practice.

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    Knowledge Management

    Knowledge is:

    Knowing

    WHYWHAT

    WHEN

    HOW

    WHERE

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    Knowledge Management

    Y KM?

    70 80 % what employees know is hidden.

    Knowledge has become the key

    differentiating factor.

    It is the most sought after resource / asset.

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    EMERGENCE

    1996 Worlds top 5 heart surgeons

    24% decrease in mortality rates

    KM is a collaborative learning

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    Definition

    Knowledge Management refers to the

    processes and/or tools an organization uses to

    collect, analyze, store, and disseminate its

    intellectual capital.

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    Knowledge Cycle

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    Sources of Knowledge

    Employees

    Products

    Customers

    Suppliers

    Competitors

    Government

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    Objectives of KM

    Create knowledge repositories

    a) External knowledge (competitive intelligence,

    market data, surveys, etc.)b) Structured internal knowledge (reports,

    marketing materials, etc.)

    c) Informal internal knowledge (discussiondatabases of know how)

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    Improve knowledge access through

    a) Technical expert referral

    b) Expert networks used for staffing based on

    individual competencies

    c) Turnkey video conferencing to foster easy

    access to distributed experts.

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    Enhance the knowledge environment

    a) Change organizational norms and values

    related to knowledge in order to

    encourage knowledge use and knowledge

    sharing

    b) Customers rating of organisations expertise

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    Manage knowledge as an asset

    a) Attempt to measure the contribution of

    knowledge to bottom line success

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    Knowledge Economy

    An Economy where the growth of GDP is

    altered based on the changes in the

    knowledge based industries.

    Ex: India IT industry falls GDP falls.

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    Knowledge Engineering

    Knowledge engineering (KE) was defined in

    1983 by Edward Feigenbaum, and Pamela

    McCorduck

    KE is an engineering discipline that involves

    integrating knowledge into engineering

    systems in order to solve complex problems

    normally requiring a high level ofhumanexpertise.

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    Knowledge Engineering - Scope

    artificial intelligence

    databases,

    data mining, expert systems,

    decision support systems and

    geographic information systems.

    cognitive science and

    socio-cognitive engineering

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    Knowledge engineering principles

    Knowledge engineers acknowledge that there aredifferent types of knowledge, and that the rightapproach and technique should be used for theknowledge required.

    Knowledge engineers acknowledge that there aredifferent types of experts and expertise, suchthat methods should be chosen appropriately.

    Knowledge engineers recognize that there aredifferent ways of representing knowledge, whichcan aid the acquisition, validation and re-use ofknowledge.

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    Knowledge engineering principles

    Knowledge engineers recognize that there are

    different ways of using knowledge, so that the

    acquisition process can be guided by the project

    aims (goal-oriented).

    Knowledge engineers use structured methods to

    increase the efficiency of the acquisition process.

    Knowledge Engineering is the process of elicitingKnowledge for many purpose be it Expert system

    or AI development

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    Views of knowledge engineering

    Transfer View This is the traditional view. In

    this view, the assumption is to apply

    conventional knowledge engineering

    techniques to transfer human knowledge into

    artificial intelligence systems.

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    Knowledge Intensive Organizations

    Employs Highly skilled staff, knowledge

    workers

    Dealing with uncertainty Requires people who are problem solvers

    Follows best practices to attract & retain

    talents Knowledge seen as an asset

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    Competence & Knowledge

    Competence is the underlying characteristics

    of a person to perform a job

    Knowledge forms the basis for the underlying

    characteristics of a person to perform a task

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    Types of Knowledge

    Domain knowledge: Knowledge about the

    objective realities in the domain ofinterest

    (Objects, relations, events, states, causalrelations, etc. that are obtained in

    some domains)

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    Problem-solving knowledge: Knowledge about

    how to use the domain knowledge to achieve

    various goals. This knowledge is often in the

    form of a problem-solving method (PSM) that

    can help achieve the goals in a different

    domain.

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    Knowledge Ontology

    The term ontology is usually defined as aformal description of the knowledge in adomain / in a generic model.

    First, ontology can refer to a full descriptionof all the knowledge, so that it can berepresented and used within a computersystem.

    Second, ontology can refer to a genericmodel that applies to a class of domains.

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    Elements of Knowledge Ontology

    (1) a set of knowledge objects

    (2) a set of relations that form associations

    (relationships) between the knowledge objects

    (3) a set of axioms that provides rules and

    constraints for the relationships (e.g. if A is next

    to B, then B is next to A). The ontology described

    here will make use of the first two elements, butnot include any axioms, which requires more

    development.

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    Y Ontology in Personal Knowledge

    First, it can help to integrate and coordinate

    the use of the Personal Knowledge Techniques

    for more efficient acquisition of knowledge

    and facilitation of self-help.

    Second, the ontology can provide a common

    underlying language that aids users to

    understand the information available to them(e.g. from other users) and aids researchers to

    compare knowledge from different users.

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    Third, the ontology can help the user when

    searching for, and being presented with,

    advice from the system. This is achieved by

    using the ontology to provide key words and

    semantic tags with which to code theinformation for searching.

    Fourth, the ontology provides a structured set

    of categories that can be used to analyse theknowledge captured from users.

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    Fifth, as multiple users make use of the

    Personal Knowledge Methodology, the

    ontology can develop to be a reflection of thecommonalities between these users lay

    psychological theories.

    Sixth, the ontology can be a contribution tothe ongoing development of ontology within

    knowledge engineering.

    Finally, a longer-term goal would be to

    develop multiple versions of the ontology

    appropriate to different populations .