Transcript Just-in-time Knowledge Flow for Distributed Organizations

Just-in-time Knowledge
Flow for Distributed
Organizations using
Agents Technology
R. Brena, J.L. Aguirre, A.C.
Treviño
ITESM, Mexico
Who are we?
Joint project between a lab in AI
and a Bussiness research center at
the ITESM, Monterrey:
Center for Artificial Intelligence
Center for Knowledge Systems
Summary
Just-in-time Knowledge
Agents technology
Architecture
Ontologies
Services
Contexts
Discussion
Conclusions
Knowledge economy
Increased relative weight of
knowledge and information in the
production of value
Knowledge is critical for shrinking
cycle time for competency-base
renewal
Pressure for most organization to
cope with massive flood of
unstructured information
Knowledge life cycle
Knowledge flow
Often K is created in one place and
needed (often not used) in another
Many large distributed
organizations suffer from a lack of
K circulation both in vertical and
horizontal directions
Good dissemination of relevant
pieces of information and
knowledge is very important
JITIK concept
“Just-in-time” Information and
Knowledge
Give support to K circulation in the
organization by connecting the
right K with the right person at the
right moment
Right Knowledge
Knowledge pieces are
characterized as points in a
multidimensional space
Dimensions are class hierarchies
These come from “ontologies”
Examples:
– Classification of users’ interest areas
– Structure of the organization
Right person
“Right knowledge” and “Right
person” are reciprocal
We use the same categories for
characterizing users and
knowledge
This makes possible to link pieces
of knowledge to corresponding
users
Right moment
 The time for sending a piece of
knowledge could be:
– When that K is generated
– When it arrives to the organization or
is discovered
– When a particular users needs it
1. The user knows he/she needs it
(point-and-click search)
2. The user is not aware of needing some
information
(K is diffused to some specific users)
Agents technology
Long-lived autonomous processes
Reactive and proactive
Cooperate and compete
Users delegate tasks to agents
(electronic assistants)
Point & Click / Delegate
Old paradigm: Point and click
– Computer does just what user directs
it to do
New paradigm: Delegate
– Computer takes care of tasks and
reports results to the master
Search / Diffuse
Usually K is searched by users
– (point and click paradigm)
In JITIK K is diffused to users as it
becomes available / relevant
– (delegation paradigm)
Architecture
Parasitic
agents
Directory
agent
Cluster
agents
Personal Agents
Cluster agents
Inference
Engine
DB
Working
data
Communication
interface
Inference engine
Forward-chaining rule-based
Rules of the form:
– Distribute K satisfying
Char(K) to U satisfying
Char(U) when E
– Distribute www_library_regulation
satisfying relevant(library_regulation,
new_users) to ?x satisfying
new_registered(?x) when NOW.
Directory agents
Directory
agent
Help finding other agents
Like DNS services
Give great flexibility to the system’s
(re)configuration
Personal agents
Take care of services specific to an
individual
Examples:
– Monitoring specific web pages
– Checking ranges for values in
databases
– Reporting articles from netnews
related to interest areas
Maintain a “user profile”
Parasitic agents
Allow JITIK to gather information
from other systems
Parasitic agents are “fastened” to
conventional programs
PA report to cluster agents
– Identity of the PA
– Event being reported
– Associated data
PA find cluster agents using DA
Knowledge/Users specification
Combination (“and”) of several
class hierarchies
Example:
– User in the sales division
(organization classification), and
– User is executive in charge of a
department (level classification), and
– User involved in best-practices
support (tasks classification), and
– User expert in customer satisfaction
(competence classification)
Ontologies
The set of class hierarchies is a
form of “ontology”
Terms are defined by their place in
class hierarchies
Expression of ontologies in an
ontology-oriented language is
under way
JITIK services
Alerts
Messages
K from bussiness processes
Alerts
Alerts are brief notification of
events:
– A new relevant piece of information
has arrived
– An important information has changed
– A deadline has been reached
They are reported to personal
agents, which notify their user
according to his/her profile
Messages
Messages are created by a human
user
The delivery time could be now or
when some conjunction of
conditions become true
Messages are delivered in a form
chosen by the user (email, instant
messaging, web)
K from bussiness processes
Parasitic Agents are attached to key
points of bussiness processes
Information from PA is associated
to a specification of relevant K
Relevant K is then distributed
among concerned users
Example: New user registers at a
library.- Send him/her regulations
JITIK in context
JITIK could be applied to a variety
of organizational contexts:
– Big distributed / multinational /
vertical entreprises
– Virtual organizations and networks
– Task forces
Best-practices support
Best practices are hard to
generalize
Quality circles run without much
automated support
JITIK can distribute best practices
to relevant users
Could help to break geografical /
organizational distances
Virtual organizations
Users are spread over the world
They share common interests /
activities (e.g. Medical specialists)
JITIK could help to distribute
relevant alerts, information and
knowledge
Discussion
Personal computers or server
networks?
– PC are not running and connected
around the clock
– Permanent tasks could not be
delegated
– Personal agents need to take care of
their delegated tasks on a permanent
basis
A word on methodology
Currently there is no methodology
to create rules relating knowledge
to users and events
Rules are themselves a form of K
about the organization (e.g.
Intellectual capital)
Project status
Web-based client-server technology
version running
Java programming
Jess inference engine
Full agent-tech version under
development
Future work
Broader scope in K life cycle
Tighter integration as KM support
tool (e.g. K maps, K monitoring)
Sophisticated AI tools (Case-based
reasoning, Data mining, Knowledge
repositories)
Integration with workflow systems
and CSCW
Integration with XML and related
technologies
Conclusions
JITIK is a method for relating a piece
of knowledge or information,
specied as mentioned, to a set of
users, also characterized in an
abstract way, when an event is
produced
JITIK provides diffusion of the right K
to the right person at the right time