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4/10: Managing Knowledge & IS
Tools for Decision-Making
• Knowledge Management
– Office & document management systems
– Knowledge work systems
– Group collaboration systems, intranet knowledge
environments
– Artificial intelligence: Expert Systems, Case-based reasoning
– Neural networks, Fuzzy logic, Genetic algorithms, Hybrid AI
systems, Intelligent agents
• Enhancing Management Decision-Making
– Decision Support Systems (DSS)
– Group DSS
– Executive Support Systems (ESS)
Knowledge Management
• “ The process of systematically and actively
managing and leveraging the stores of
knowledge in an organization.”
• An organization’s knowledge base may include:
– Structured internal knowledge
– External knowledge
– Informal internal knowledge (tacit knowledge)
Information Work
• “Work that primarily consists of creating or
processing information.”
• Two types of workers:
– Data workers: those who
process & disseminate
information & paperwork.
– Knowledge workers: those
who create knowledge;
those who design products
& services.
Office & Document Management
Systems
• 3 basic functions of an office:
– Managing & coordinating the work of data &
knowledge workers
– Connecting the work of the local info workers with
the larger organization
– Connecting the organization to the
external environment
Office Workers: Activities
• Managing documents
– Document creation, storage, retrieval, dissemination
• Scheduling for individuals & groups
• Communicating for individuals & groups
– Voice,digital, & document-based communications
• Managing data
Office Systems Help Office Workers
• “Computer systems, such as word processing,
voice mail, and imaging that are designed to
increase productivity of office workers.”
• Help with:
–
–
–
–
Document creation, dissemination, & retrieval
Collaboration
Scheduling
Etc.
Document Imaging Systems
• Convert printed documents & images to digital
form for storage & access by computer.
• Not-often-used documents can be stored on a
jukebox (optical disk system w/ multiple disks).
• Alternative to DIS: Intranets
– Workers publish documents to web-based form
directly
Knowledge Work Systems
• “Information systems that aid knowledge
workers in the creation and integration of new
knowledge in the organization.”
• 3 key roles for knowledge workers:
– Keeping the organization up to date with knowledge
in external world
– Serving as internal consultants in their areas of
expertise
– Acting as change agents to evaluate, initialize, &
promote change.
Requirements for KWS
• Specialized tools needed for particular task
• User-friendly interface
• Access to external databases
• Examples of KWS:
– CAD
– Virtual reality systems, VRML systems
– Investment workstations
CAD: Computer-Aided Design
• Automates creation & modification of designs
by using computers.
Virtual Reality, VRML Systems
• Have visualization, rendering, and simulation
capabilities beyond conventional CAD.
• VRML: Virtual Reality Markup Language
– Virtual reality designed for the Web
Group Collaboration Systems
• Groupware
– “Software that provides functions and services that
support the collaborative activities of workgroups.”
– Examples:
•
•
•
•
publishing: tracking multiple users’ edits to a document
replication: keeping identical data on multiple PCs
discussion tracking
security: preventing unauthorized access to data
Group Collaboration Systems
• Intranet knowledge environments
– An alternative to traditional groupware
– Cheaper, easier to maintain for email, discussion
groups, multimedia Web documents
• Which to choose?
– Groupware: projects requiring extensive
coordination & management, editing on the fly,
tracking revisions, greater security
– Intranet: simple tasks like sharing documents, email,
publishing documents, etc.
Artificial Intelligence
• “The effort to develop computer-based systems that
behave like humans.” (inc. hardware & software)
• AI systems are based on human expertise, knowledge,
and selected reasoning patterns, but do not exhibit
human intelligence.
• Why would businesses want this science-fiction idea?
–
–
–
–
–
to preserve expertise that may be lost
to store information in an active form
to create a mechanism invulnerable to human feelings
to eliminate boring & unsatisfying jobs
to enhance an organization’s knowledge base by providing
interactivity.
Expert Systems
• “Knowledge-intensive computer program that
captures the expertise of a human in limited
domains of knowledge.”
• Narrow & brittle
• Perform tasks that a professional could do in a
few minutes or hours.
Expert Systems: Parts
• Knowledge base: model of human knowledge
used by ES.
• Rule base: the part of the knowledge base that is
contained in IF/THEN structures.
• Knowledge frames: organizes knowledge into
chunks of interrelated characteristics.
• AI shell: programming environment of an ES.
• Knowledge engineer: a systems analyst expert in
converting human knowledge into an ES.
Case-based reasoning
• “Artificial intelligence technology that
represents knowledge as a database of cases and
solutions.”
• Each new case is compared with existing cases
to suggest a solution. Each new case is added to
the database of cases upon arriving at a
satisfactory solution.
Other Intelligent Techniques
• Neural networks
– attempt to emulate the processing patterns of the
biological brain; have a general capacity to learn.
• Fuzzy logic
– rule-based AI that tolerates imprecision using
membership functions.
• Genetic algorithms
– Solution evolves through mutation, adaptation, and
natural selection out of possible answers.
Intelligent agents
• “Software that uses a built-in or learned
knowledge base to carry out specific, repetitive,
and predictible tasks for the user, business
process, or other software application.”
• Example uses:
–
–
–
–
wizards in MS Office
delete junk email
find cheapest airfare
search auctions for lowest price on item
• Bots – http://www.mySimon.com
Enhancing Management DecisionMaking
• Decision Support Systems (DSS)
– “Computer systems for management that combines
data, analytical tools, and models to support semistructured and unstructured decision-making.
– MIS are predefined management reports, etc., not
unstructured.
Two types of DSS
• Model-driven DSS
– “Primarily stand-alone system that uses a model to
perform “what-if” analysis.”
• Data-driven DSS
– “A system that allows users to extract & analyze
information in large databases.”
Data-driven DSS: Datamining
• Associations: things linked to a single event.
• Sequences: events linked over time.
• Classification: patterns that describe a group,
inferring a set of rules.
• Clustering: like classification, but no defined
group yet exists.
• Forecasting: using a series of values to forecast
what other values may be.
Parts of a DSS
• Database: all the data
– historical and/or current from various applications.
• Software system
– Software tools used for analysis.
• Examples inc.
web-based DSS
Examples of DSS
•
•
•
•
American Airlines: price & route selection
Frito-Lay: price, advertising, & promotion mix
Texas Oil & Gas: evaluation of drilling sites
General Accident Insurance: fraud detection
Group DSS
• “An interactive computer-based system that
facilitates solutions to unstructured problems by
decision-makers working as a group.”
• Parts:
– Hardware: conference facility itself, PCs, overheads,
etc.
– Software tools: electronic questionnaires,
brainstorming tools, voting tools, etc.
– People
Executive Support Systems (ESS)
• “Information systems for strategic-level
unstructured decision-making in an organization
through advanced graphics & communications.”
• Drilling down: ability to move from summary
data to lower and lower levels of detail.
Benefits of ESS
• Easy to use; little training needed.
• Ability to analyze, compare, and highlight
trends.
• Enhance quality of decision-making because of
drill-down capability