Web-based Learning Solutions for Communities of Practice

Mining Unnoticed Knowledge in Collaboration Support Systems
network analysis has been a research area applied
for several decades on organizations. In business,
SNA can be a useful tool to reveal relationships
and organizational structure beneath the ones formally
defined. Those relationships are extracted
by examining the communication level among
employees, resulting to a related graph. The
outcome of this graph analysis is likely to result
to a flow chart that does not necessarily follow
the formal organizational structure. Traditionally,
those relationships are revealed by acquiring
data manually either through questionnaires or
interviews. SNA has been applied with success in
business for decades and is regarded a useful tool
to analyze how a corporate functions. This includes
identifying employees that are “key players” in
the communication flow of the company.
In recent years, a large number of web sites
aiming at easing online communication forming
virtual communities –not necessarily with a special
goal or context- have been deployed. Popular
web sites like friendster (http://www.friendster.
com claimed to have 5 million users by 2003),
facebook (http://www.facebook.com claims
to have over 100 million users currently) and
myspace (http://www.myspace.com has reached
100 million users on 2006) have attracted a vast
number of users. In order to increase a user’s
network, contemporary systems are using “friend
of friend” approach. This approach is based on
the reasonable hypothesis that if two users share
one or more common friends, those users are
very likely to have some kind of connection or
relationship between them as well.
From a more technological approach, on
2000 a technology was deployed called “Friend
of Friend”, which is an extension of Resource
Description Framework (RDF), specified with
Web Ontology Language (OWL). This solution
has received great appraise and may be considered
a part of the effort to enhance Web with more
semantics (Semantic Web). It is worth noting
that -within this context- Tim Berners Lee has
coined up with the title Giant Global Graph as
the graph that unites both World Wide Web and
Social Graph (Lee 2007). The past four years,
research based on the above technology has been
conducted (Paolillo 2004), (Mika, 2005). Research
work mainly focuses on technological solutions
that exploit the FOAF (http://www.foaf-project.
org/) standard in order to create large organized
information concerning users. For example, Flink
(Mika, 2005) “is a presentation of the professional
work and social connectivity of Semantic Web
researchers”. Through a set of components that
mine information sources like FOAF profiles,
web pages, publication archives (e.g. through
Google or Google Scholar) the system is aiming
at presenting over the web the community under
investigation. It is worth noting that similar research
concerning scientific research has been
conducted by examining co-authorship or citations
(Barabási, 2002).
From a more formal perspective, data mining
can play an important role in the area of collaboration
systems, in that it can provide advanced
awareness about diverse community activities.
Data mining in these systems can be defined as
the effort to generate actionable models through
automated analysis of their databases. Data mining
can only be deployed successfully when it generates
insights that are substantially deeper than
what a simple view of data can give. Clustering is
one of the basic data mining techniques (Han &
Kamber, 2001), (Hand, Mannila & Smyth, 2000),
on which numerous approaches have been proposed.
Generally speaking, the goal of clustering
is, given a dataset, to find “naturally” occurring
groups within this dataset. With the rapid increase
in web-traffic, understanding user behavior based
on their interaction with a website is becoming
more and more important for website owners.
Clustering in correlation with personalization
techniques of this information space has become
a necessity. Web-based systems (including collaboration
systems) can have mechanisms with
multiple ways to report on events, conditions,
errors and alerts. In addition, when we have to
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