My first exposure to Support Vector Machines came this spring when heard Sue Dumais present impressive results on text categorization using this analysis technique. This issue's collection of essays should help familiarize our readers with this interesting new racehorse in the Machine Learning stable. Bernhard Scholkopf, in an introductory overview, points out that a particular…
IEEE Intelligent Systems and their Applications Template
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About the IEEE Intelligent Systems and their Applications format
IEEE Intelligent Systems and their Applications is a peer-reviewed journal published by IEEE, covering Semantic Web and Ontologies, AI-based Problem Solving and Planning, Advanced Database Systems and Queries.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Intelligent Systems and their Applications, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in IEEE Intelligent Systems and their Applications style. No sign-up. |
| Publishes research in | Semantic Web and Ontologies AI-based Problem Solving and Planning Advanced Database Systems and Queries Service-Oriented Architecture and Web Services Data Mining Algorithms and Applications |
| ISSN | 1094-7167 |
| h-index | 66 |
| i10-index | 155 |
| Total citations | 25,506 |
| Top institutions publishing here | Carnegie Mellon University |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
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Most-cited papers in IEEE Intelligent Systems and their Applications
This survey provides a conceptual introduction to ontologies and their role in information systems and AI. The authors also discuss how ontologies clarify the domain's structure of knowledge and enable knowledge sharing.
Practical pattern-classification and knowledge-discovery problems require the selection of a subset of attributes or features to represent the patterns to be classified. The authors' approach uses a genetic algorithm to select such subsets, achieving multicriteria optimization in terms of generalization accuracy and costs associated with the features.
Self-adaptive software requires high dependability robustness, adaptability, and availability. The article describes an infrastructure supporting two simultaneous processes in self-adaptive software: system evolution, the consistent application of change over time, and system adaptation, the cycle of detecting changing circumstances and planning and deploying responsive modifications.
Methontology provides guidelines for specifying ontologies at the knowledge level, as a specification of a conceptualization. ODE enables ontology construction, covering the entire life cycle and automatically implementing ontologies. To meet the challenge of building ontologies, we have developed Methontology, a framework for specifying ontologies at the knowledge level, and the Ontology Development Environment. We…