This document provides an overview of modeling concepts for service-based software architectures (SBSAs). The concepts were extracted during a survey of conceptual frameworks for architecture modeling of SBSAs.

Knowledge discovery support environments include beside classical data analysis tools also data mining tools. For supporting both kinds of tools, a unified knowledge representation is needed. We show that concept lattices which are used as knowledge representation in Conceptual Information Systems can also be used for structuring the results of mining association rules. Vice versa, we use ideas of association rules for reducing the complexity of the visualization of Conceptual Information Systems.

Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper proposes the use of graph clustering techniques on ...

Wissensmanagement in zentralisierten Wissensbasen erfordert einen hohen Aufwand für Erstellung und Wartung, und es entspricht nicht immer den Anforderungen der Benutzer. Wir geben in diesem Kapitel einen Überblick über zwei aktuelle Ansätze, die durch kollaboratives Wissensmanagement diese Probleme lösen können. Im Peer-to-Peer-Wissensmanagement unterhalten Benutzer dezentrale Wissensbasen, die dann vernetzt werden können, um andere Benutzer eigene Inhalte nutzen zu lassen. Folksonomies versprechen, die ...

As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures ...

Association rules are a popular knowledge discovery technique for warehouse basket analysis. They indicate which items of the warehouse are frequently bought together. The problem of association rule mining has first been stated in 1993. Five years later, several research groups discovered that this problem has a strong connection to Formal Concept Analysis (FCA). In this survey, we will first introduce some basic ideas of this connection along a specific algorithm, TITANIC, and show how FCA helps in reducing the ...

Ein wichtiger Baustein des neu entdeckten World Wide Web - des "Web 2.0" - stellen Folksonomies dar. In diesen Systemen können Benutzer gemeinsam Ressourcen verwalten und mit Schlagwörtern versehen. Die dadurch entstehenden begrifflichen Strukturen stellen ein interessantes Forschungsfeld dar. Dieser Artikel untersucht Ansätze und Wege zur Entdeckung und Strukturierung von Nutzergruppen ("Communities") in Folksonomies.

Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.

Ontologies have been established for knowledge sharing and are widely used as a means for conceptually structuring domains of interest. With the growing usage of ontologies, the problem of overlapping knowledge in a common domain becomes critical. In this short paper, we address two methods for merging ontologies based on Formal Concept Analysis: FCA-Merge and ONTEX. --- FCA-Merge is a method for merging ontologies following a bottom-up approach which offers a structural description of the merging process. The method ...

Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. This survey analyzes the convergence of trends from both areas: an increasing number of researchers is working on improving the results of Web Mining by exploiting semantic structures in the Web, and they make use of Web Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself. The Semantic Web is the second-generation WWW, enriched ...