Concept Mining with Self-Organizing Maps for the Semantic Web

Authors:
Timo Honkela;Matti Pöllä
Affiliations:
Department of Information and Computer Science Adaptive Informatics Research Centre, Helsinki University of Technology, TKK, Finland FI-02015;Department of Information and Computer Science Adaptive Informatics Research Centre, Helsinki University of Technology, TKK, Finland FI-02015
Venue:
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
Year:
2009

Citing 10
Cited 1

The vocabulary problem in human-system communication

Communications of the ACM
The symbol grounding problem

CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Implementing expert system rule conditions by neural networks

New Generation Computing
CYC: a large-scale investment in knowledge infrastructure

Communications of the ACM
Self-Organizing Maps

Self-Organizing Maps
Mining massive document collections by the WEBSOM method

Information Sciences: an International Journal - Special issue: Soft computing data mining
The pragmatic web: a manifesto

Communications of the ACM - Two decades of the language-action perspective
Soft Computing in Ontologies and Semantic Web (Studies in Fuzziness and Soft Computing)

Soft Computing in Ontologies and Semantic Web (Studies in Fuzziness and Soft Computing)
Clustering of the self-organizing map

IEEE Transactions on Neural Networks
PicSOM-self-organizing image retrieval with MPEG-7 content descriptors

IEEE Transactions on Neural Networks

A model for human-computer interaction in the semantic web

Proceedings of the 7th International Conference on Semantic Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we discuss problems related to the basic Semantic Web methodologies that are based on predicate logic and related formalisms. We discuss complementary and alternative approaches. In particular, we suggest how the Self-Organizing Map can be a basis for making the Semantic Web more semantic.