Proceedings of the 12th European Conference on Knowledge ...

Andrea Kő, Péter Fehér and Krisztián Varga
and discover knowledge elements, ICT solutions can be used, which focus on not <strong>the</strong> storage <strong>of</strong>
knowledge elements, ra<strong>the</strong>r on creating a map <strong>of</strong> <strong>the</strong> intellectual capital and competences in an
organization (Davenport and Prusak, 1999). It is possible to reach <strong>the</strong> experts, “localize” <strong>the</strong>m (e.g.
with knowledge maps). In this way it facilitates <strong>the</strong> distribution <strong>of</strong> knowledge. Intelligent agents
automate <strong>the</strong> identification <strong>of</strong> important and valuable knowledge elements (Malone et al, 1997), while
discussion forums and chat rooms can be used to collect knowledge from its origin: <strong>the</strong> people
<strong>the</strong>mselves (Pan and Scarbrough, 1998).
To support creation <strong>of</strong> new knowledge, data mining, OLAP-based techniques, statistical or o<strong>the</strong>r
analytical tools are useful (Shaw et al, 2001). Organizations can use decision support systems, data
warehouses, expert systems, data mining tools to treat and analyse input and output variables,
processes that are related to each o<strong>the</strong>r in complex way; to process and use huge amount <strong>of</strong>
information in decision-making and statistic analysis. As part <strong>of</strong> <strong>the</strong> data mining process, neural
networks can play an important role. Neural networks model <strong>the</strong> neurons <strong>of</strong> <strong>the</strong> human brain, and use
ma<strong>the</strong>matical rules and formulas in order to make decisions or find new knowledge elements (Lin and
Shaw, 1997). Ano<strong>the</strong>r popular way to discover new pieces <strong>of</strong> knowledge in an organization is text
mining, when information and knowledge are searched beneath <strong>the</strong> meaning, “between <strong>the</strong> lines” <strong>of</strong>
documents, e-mails, etc. (Lang and Burnett, 2000; Abecker et al, 2000; Ahmed and Ward, 2000, Rao
and Sprague, 1998).
To share and deliver knowledge IT <strong>of</strong>fers <strong>the</strong> usage <strong>of</strong> search engines, enterprise portals or document
management systems (Simon, 2001). In case <strong>of</strong> explicit knowledge an online, central repository can
be developed supporting <strong>the</strong> search and access <strong>of</strong> information for anybody who requires it.
Employees not only can read <strong>the</strong> information stored in <strong>the</strong> repositories, <strong>the</strong>y can share <strong>the</strong>ir own
experiences and knowledge as well.
The information technology has an important role in <strong>the</strong> uncertainty management (e.g. fuzzy
systems). The development <strong>of</strong> organizational ontology can solve <strong>the</strong> problems related to <strong>the</strong>
ambiguity mentioned above (Abecker et al. 1998; O’Leary, 1998). Primarily specifying <strong>the</strong> meaning <strong>of</strong>
<strong>the</strong> occurring expressions more accurately, than <strong>the</strong> natural language provides it. It has <strong>the</strong>
advantage <strong>of</strong> supporting <strong>the</strong> realization <strong>of</strong> consistency and completeness.
More areas <strong>of</strong> KM can be supported with groupware systems. These systems helps <strong>the</strong>ir users to
collaborate, and in this way, to create, share and use new, common knowledge elements (Gábor,
2002, Hayes and Walsham, 2001). Solutions supporting collaborative work assist <strong>the</strong> learning
process <strong>of</strong> <strong>the</strong> organization (e.g. Lotus Notes).
Expert systems are useful in <strong>the</strong> phase <strong>of</strong> using <strong>the</strong> existing (or discovered, newly created) knowledge
(Liebowitz and Beckman, 1998).
Workflows or o<strong>the</strong>r automated processes may pr<strong>of</strong>it from <strong>the</strong> usage <strong>of</strong> a knowledge-based system,
like a repository, ontology or expert system. In an activity, a query can be defined, <strong>the</strong> knowledgebased
system may support explicit knowledge as answer, and this, combined with <strong>the</strong> knowledge <strong>of</strong>
<strong>the</strong> user will form a new solution to <strong>the</strong> main question (Salisbury, 2003).
The expression “Knowledge management system” also occurs in <strong>the</strong> literature. Schreiber has <strong>the</strong>
following definition (Schreiber et al, 1998): <strong>the</strong> knowledge management system is a tool for managing
<strong>the</strong> organizational knowledge, supporting organizations in problem-solving activities and facilitating
<strong>the</strong> decision-making.
The application <strong>of</strong> technology is not enough for <strong>the</strong> development <strong>of</strong> <strong>the</strong> knowledge intensive
environment. It has an important role in <strong>the</strong> knowledge management life cycle, but it cannot guarantee
<strong>the</strong> organizational success in <strong>the</strong> area <strong>of</strong> knowledge management. The technology is a vital element
<strong>of</strong> knowledge management, but it does not equal to it.
Knowledge management projects <strong>of</strong>ten rely on <strong>the</strong> latest technologies and in some cases <strong>the</strong>y act as
a catalyst in knowledge management initiatives. Information and communication technologies have
mainly supporting role in knowledge codification; transfer, sharing and utilization, but sometimes <strong>the</strong>y
get a decisive role in knowledge management processes. Several frameworks are available in <strong>the</strong>
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