Interactive Use of Inductive Approach for Analyzing and Developing Conceptual Structures

Sixth International Conference on Research Challenges in Information Science (RCIS 2012): Conference Proceedings 2012
Ilze Birzniece

Inductive learning algorithms learns classification from training examples and uses induced classifier for dealing with new instances. The use of conceptual data structures for classifier’s input is making this task more complicated and classifier may meet the difficulties in class prediction. To broaden applicability of inductive learning based classifiers a collaborative approach between the system and human expert would be useful. The proposed interactive system in uncertain conditions can ask for human advice and improve its knowledge base with the rule derived from this interaction. Interactive inductive learning based classification system is proposed for helping to compare university study courses semi-automatically

Keywords
inductive learning; human-computer interaction; study course comparison; conceptual structures
DOI
10.1109/RCIS.2012.6240453
Hyperlink
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6240453

Birzniece, I. Interactive Use of Inductive Approach for Analyzing and Developing Conceptual Structures. In: Sixth International Conference on Research Challenges in Information Science (RCIS 2012): Conference Proceedings, Spain, Valencia, 16-18 May, 2012. Piscataway: IEEE, 2012, pp.129-134. ISBN 978-1-4577-1936-3. e-ISBN 978-1-4577-1937-0. ISSN 2151-1349. Available from: doi:10.1109/RCIS.2012.6240453

Publication language
English (en)