CAMLET: A platform for automatic composition of inductive learning systems using ontologies

Akihiro Suyama, Naoya Negishi, Takahira Yamaguchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

Here is presented a platform for automatic composition of inductive learning systems using ontologies called CAMLET, based on knowledge modeling and ontologies engineering technique. CAMLET constructs an inductive applications with better competence to a given data set, using process and object ontologies. Afterwards, CAMLET instantiates and refines a constructed system based on the following refinement strategies: greedy alteration, random generation and heuristic alteration. Using the UCI repository of ML databases and domain theories, experimental results have shown us that CAMLET supports a user in constructing a inductive applications with best competence.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages205-215
Number of pages11
Volume1531
ISBN (Print)354065271X, 9783540652717
DOIs
Publication statusPublished - 1998
Externally publishedYes
Event5th Pacific Rim Intemational Conference on Artificial Intelligence, PRICAI 1998 - Singapore, Singapore
Duration: 1998 Nov 221998 Nov 27

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1531
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other5th Pacific Rim Intemational Conference on Artificial Intelligence, PRICAI 1998
CountrySingapore
CitySingapore
Period98/11/2298/11/27

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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    Suyama, A., Negishi, N., & Yamaguchi, T. (1998). CAMLET: A platform for automatic composition of inductive learning systems using ontologies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1531, pp. 205-215). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1531). Springer Verlag. https://doi.org/10.1007/BFb0095270