Fensel, D.; Lausen, H.; Polleres, A.; Bruijn, J. D.; Stollberg, M.; Roman, D. & Domingue, J. (Hrsg.): Enabling Semantic Web Services: The Web Service Modeling Ontology. Heidelberg: Springer-Verlag, 2006

Hepp, M.; Bachlechner, D. & Siorpaes, K.: Harvesting Wiki Consensus - Using Wikipedia Entries as Ontology Elements. In: Völkel, M. & Schaffert, S. (Hrsg.): Proceedings of the First Workshop on Semantic Wikis - From Wiki to Semantics, co-located with the 3rd Annual European Semantic Web Conference (ESWC 2006). ESWC2006, 2006Workshop on Semantic Wikis
[Volltext]

existing Web content is the lack of domain ontologies. While FOAF

and Dublin

Core are popular means for expressing relationships between Web resources

and between Web resources and literal values, we widely lack unique

identifiers

for common concepts and instances. Also, most available ontologies

have a

very weak community grounding in the sense that they are designed

by single

individuals or small groups of individuals, while the majority of

potential users

is not involved in the process of proposing new ontology elements

or achieving

consensus. This is in sharp contrast to natural language where the

evolution of

the vocabulary is under the control of the user community. At the

same time,

we can observe that, within Wiki communities, especially Wikipedia,

a large

number of users is able to create comprehensive domain representations

in the

sense of unique, machine-feasible, identifiers and concept definitions

which are

sufficient for humans to grasp the intension of the concepts. The

English

version of Wikipedia contains now more than one million entries and

thus the

same amount of URIs plus a human-readable description. While this

collection

is on the lower end of ontology expressiveness, it is likely the

largest living

ontology that is available today. In this paper, we (1) show that

standard Wiki

technology can be easily used as an ontology development environment

for

named classes, reducing entry barriers for the participation of users

in the

creation and maintenance of lightweight ontologies, (2) prove that

the URIs of

Wikipedia entries are surprisingly reliable identifiers for ontology

concepts, and

(3) demonstrate the applicability of our approach in a use case.

Hepp, M.; Siorpaes, K. & Bachlechner, D.: Towards the Semantic Web in e-Tourism: Lack of Semantics or Lack of Content?. Poster Proceedings of the 3rd Annual European Semantic Web Conference (ESWC 2006). Budva, Montenegro: 2006
[Volltext]

Hotho, A.; Jäschke, R.; Schmitz, C. & Stumme, G.: Emergent Semantics in BibSonomy.. In: Hochberger, C. & Liskowsky, R. (Hrsg.): GI Jahrestagung (2). GI, 2006 (LNI 94), S. 305-312
[Volltext]

Lambiotte, R. & Ausloos, M.: Collaborative tagging as a tripartite network. In: Lecture Notes in Computer Science (2006), Nr. 3993, S. 1114 - 1117
[Volltext]

Schmitz, C.; Hotho, A.; Jäschke, R. & Stumme, G.: Mining Association Rules in Folksonomies. In: Batagelj, V.; Bock, H.-H.; Ferligoj, A. & Žiberna, A. (Hrsg.): Data Science and Classification. Proceedings of the 10th IFCS Conf.. Heidelberg: Springer, 2006Studies in Classification, Data Analysis, and Knowledge Organization , S. 261-270
[Volltext]

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.