Collective Intelligence with Visualization and
J.UCS Special Issue
Jason J. Jung
(Knowledge Engineering Laboratory
Department of Computer Engineering
Yeungnam University, Korea
The aim of collective intelligence is to integrate single
intelligence of individuals for dealing with highly complex problems
[Lévy 1994]. In practice, Web 2.0 applications
like blogs and wikis have been developed to implement the collective
intelligence. Such influences by collective intelligence have been an
important issue in various knowledge-enhanced applications, e.g.,
information retrieval [Jung 2009a], semantic
web [Jung 2008b], Jung
2008a], e-business [Jung 2009c], and
e-learning [Gan and Zhu 2007, Jung 2009b].
The first paper in
this issue, authored by Grzegorz J. Nalepa, proposes a semantic wiki
platform, called PlWiki, for collaborative knowledge engineering. The
wiki system can provide a strong knowledge representation capability
for reasoning with Horn clauses-based representation. The main idea of
this system is to use Prolog clauses on the lower level to represent
facts and relations, as well as define rules on top of them.
As another important issue in semantic wiki systems, the second paper authored
by Dosam Hwang et al. introduces a consensus selection method for
reconciling conflicted knowledge. The knowledge dynamics patterns have
been classified within semantic wikis.
In the third
paper, Monika Lanzenberger et al. presents a novel ontology
alignment visualization system. Ontology has been regarded as an
important knowledge resources for collective intelligence. Thus, the
paper claims that an efficient visualization tool is needed to improve
the understandability of human users.
This special issue has been achieved by a number of fruitful
collaborations. We would like to thank the editor in chief of Journal
of Universal Computer Science (J.UCS), Hermann Maurer, for his kind
support and help during the entire process of publication. The special
issue has selected 3 high-quality papers out of 19 submissions (about
15.8% acceptance rate). This was possible thanks to the work of the
renowned researchers that provided their anonymous reviews.
Finally, we are most grateful to the authors for their valuable
contributions and for their willingness and efforts to improve their
papers in accordance with the reviewers suggestions and comments.
Jason J. Jung
(Gyeongsan, Korea, March 2010)
[Gan and Zhu 2007] Gan, Y. and Zhu, Z.: A
learning framework for knowledge building and collective wisdom
advancement in virtual learning communities. Educational Technology
& Society, 10(1):206-226, 2007.
[Jung 2008a] Jung, J.J.: Ontology-based
context synchronization for ad-hoc social
collaborations. Knowledge-Based Systems, 21(7):573-580, 2008.
[Jung 2008b] Jung, J.J.: Query transformation
based on semantic centrality in semantic social network. Journal of
Universal Computer Science, 14(7):1031-1047, 2008.
[Jung 2009a] Jung, J.J.: Contextualized query
sampling to discover semantic resource descriptions on the
web. Information Processing & Management, 45(2):283-290, 2009.
[Jung 2009b] Jung, J.J.: Semantic business
process integration based on ontology alignment. Expert Systems
with Applications, 36(8):11013-11020, 2009.
[Jung 2009c] Jung, J.J.: Social grid platform
for collaborative online learning on blogosphere: a case study of
eLearning@BlogGrid. Expert Systems with Applications,
[Levy 1994] Lévy, P.: Collective
Intelligence: Mankind's Emerging World in Cyberspace. Basic Books,