Inference in Hierarchical Multidimensional Space
Alexandr Savinov
2012
Abstract
In spite of its fundamental importance, inference has not been an inherent function of multidimensional models and analytical applications. These models are mainly aimed at numeric analysis where the notion of inference is not well defined. In this paper we define inference using only multidimensional terms like axes and coordinates as opposed to using logic-based approaches. We propose an inference procedure which is based on a novel formal setting of nested partially ordered sets with operations of projection and de-projection.
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in Harvard Style
Savinov A. (2012). Inference in Hierarchical Multidimensional Space . In Proceedings of the International Conference on Data Technologies and Applications - Volume 1: DATA, ISBN 978-989-8565-18-1, pages 70-76. DOI: 10.5220/0004039000700076
in Bibtex Style
@conference{data12,
author={Alexandr Savinov},
title={Inference in Hierarchical Multidimensional Space},
booktitle={Proceedings of the International Conference on Data Technologies and Applications - Volume 1: DATA,},
year={2012},
pages={70-76},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004039000700076},
isbn={978-989-8565-18-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Data Technologies and Applications - Volume 1: DATA,
TI - Inference in Hierarchical Multidimensional Space
SN - 978-989-8565-18-1
AU - Savinov A.
PY - 2012
SP - 70
EP - 76
DO - 10.5220/0004039000700076