Detail publikace

Text Mining Services for Trialogical Learning

SMRŽ, P. PARALIČ, J. SMATANA, P. FURDÍK, K.

Originální název

Text Mining Services for Trialogical Learning

Anglický název

Text Mining Services for Trialogical Learning

Jazyk

en

Originální abstrakt

The paper describes the architecture of Text Mining services for the Knowledge Practices Laboratory (KP-Lab). The Trialogical Learning and Activity Theory, as a new paradigm of e-Learning, stands behind the KP-Lab system. This approach requires active goal-oriented participation of learners, sharing of learning materials (knowledge artefacts), distributed and highly customizable learning environment, and knowledge-based exchange of information (practices, artefacts) among learners. The Semantic Web Knowledge Middleware was designed as a service layer for storage, maintenance, and interfacing of semantically annotated knowledge artefacts. Since artefacts and their annotations contain descriptions in natural language, the Text Mining services were devised to provide an intelligent access and manipulation with repository of artefacts. Design principles and implementation of supervised and non-supervised text mining methods for the extraction of conceptual maps and classification of knowledge artefacts are discussed in this paper.

Anglický abstrakt

The paper describes the architecture of Text Mining services for the Knowledge Practices Laboratory (KP-Lab). The Trialogical Learning and Activity Theory, as a new paradigm of e-Learning, stands behind the KP-Lab system. This approach requires active goal-oriented participation of learners, sharing of learning materials (knowledge artefacts), distributed and highly customizable learning environment, and knowledge-based exchange of information (practices, artefacts) among learners. The Semantic Web Knowledge Middleware was designed as a service layer for storage, maintenance, and interfacing of semantically annotated knowledge artefacts. Since artefacts and their annotations contain descriptions in natural language, the Text Mining services were devised to provide an intelligent access and manipulation with repository of artefacts. Design principles and implementation of supervised and non-supervised text mining methods for the extraction of conceptual maps and classification of knowledge artefacts are discussed in this paper.

Dokumenty

BibTex


@inproceedings{BUT26064,
  author="Pavel {Smrž} and Ján {Paralič} and Peter {Smatana} and Karol {Furdík}",
  title="Text Mining Services for Trialogical Learning",
  annote="The paper describes the architecture of Text Mining services for the Knowledge
Practices Laboratory (KP-Lab). The Trialogical Learning and Activity Theory, as a
new paradigm of e-Learning, stands behind the KP-Lab system. This approach
requires active goal-oriented participation of learners, sharing of learning
materials (knowledge artefacts), distributed and highly customizable learning
environment, and knowledge-based exchange of information (practices, artefacts)
among learners. The Semantic Web Knowledge Middleware was designed as a service
layer for storage, maintenance, and interfacing of semantically annotated
knowledge artefacts. Since artefacts and their annotations contain descriptions
in natural language, the Text Mining services were devised to provide an
intelligent access and manipulation with repository of artefacts. Design
principles and implementation of supervised and non-supervised text mining
methods for the extraction of conceptual maps and classification of knowledge
artefacts are discussed in this paper.",
  address="VŠB-Technical University of Ostrava",
  booktitle="Proceedings of the 6th Annual Conference Znalosti",
  chapter="26064",
  howpublished="print",
  institution="VŠB-Technical University of Ostrava",
  year="2007",
  month="february",
  pages="97--108",
  publisher="VŠB-Technical University of Ostrava",
  type="conference paper"
}