Web-based Learning Solutions for Communities of Practice

do with web-based collaboration systems, we can
consider even the common log files about users’
requests. The combination of this information
and the use of data mining techniques can help
us analyze users’ activities in depth.
In summary, the need for extracting and analyzing
relationships among users has been in play for
a long time. It can be claimed that there are two
different approaches that are rather supplementary
to the topic of the present work. One discipline
adopts traditional Social Network Analysis with
sophisticated and complex techniques for gathering
required knowledge. This approach is applied
to specific organizations aiming at revealing
issues like management or human resource vulnerabilities.
The other discipline is making use
of Semantic Web technologies, which includes a
rather one-dimensional approach (FOAF) which
may scale for the whole Social Graph.
Based on the above research, we present a web
system that is been provided to an online Community
of Practice and through the adoption of
both Data Mining and Social Network Analysis
techniques, we describe a related framework.
A NEW FRAMEWORK
In this section, we provide a brief description of
the basic characteristics of a collaboration support
system. Our approach may be applied to any
software platform that supports collaboration
through exchange of documents. We also propose
a set of metrics that can be found useful to analyze
diverse CoPs.
Description
The system we prescribe is a web application,
where users are able to create workspaces. Workspace
is a term coined to define an entity that
resides under specific CoPs and can be perceived
as a placeholder for various artifacts. For instance,
each workspace may be identified by its specific is-
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Mining Unnoticed Knowledge in Collaboration Support Systems
sue topic and users may contribute with questions,
ideas and comments (or any other collaboration
item). These user-contributed information units
may be regarded as explicit documents. Users are
able to rate each document to a scale from 1 to 5.
Document rating is optional, but is a mechanism
which will enable us to extract information concerning
the CoP members’ affinity.
Definitions:
•
We define DocumentRate as a numerical to
describe rating submitted on a document k
created by user j and rated by user i.
DocumentRate ij (k) (1)
• We define Affinity to describe user-us-
ij
er ranking from user i to user j within a
workspace.
Affinity ij = Avg(DocumentRate ij (k)) (2)
where k is every document created by user
j and has been rated by user i.
• We define Relationship to indicate the
ij
existence or not of a relationship between
user i and user j.
Relationship ij
where
ìï
1
= í
ï
ï0
îï
when A ³ t
ij
when A £ t
ij
(3)
A ij = |{DocumentRate ij (k)}|+
|{DocumentRate ji (k)}| (4)
and DocumentRate ≠ nullA is used to express
the number of ratings exchanged between
users i and j for every document k and t is a
threshold which is parameterized according
to the current needs of the community that
we analyze.For these numericals, we notice