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Author: Andrzej Wichert

Affiliation: INESC-ID/IST and Technical University of Lisboa, Portugal

Keyword(s): High Dimensional Indexing, Multi-resolution, Quantization, Vector Data Bases.

Related Ontology Subjects/Areas/Topics: Agents ; Applications of Expert Systems ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial Applications of Artificial Intelligence ; Intelligent Agents ; Internet Technology ; Methodologies and Methods ; Neural Network Software and Applications ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Non-Relational Databases ; Pattern Recognition ; Physiological Computing Systems ; Problem Solving ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods ; Web Information Systems and Technologies

Abstract: We propose a coding mechanism for less costly exact vector retrieval for data bases representing vectors. The search starts at the subspace with the lowest dimension. In this subspace, the set of all possible similar vectors is determined. In the next subspace, additional metric information corresponding to a higher dimension is used to reduce this set. We demonstrate the method performing experiments on image retrieval on one thousand gray images of the size 128×96. Our model is twelve times less complex than a list matching.

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Paper citation in several formats:
Wichert, A. (2012). Product Quantization for Vector Retrieval with No Error. In Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-8565-10-5; ISSN 2184-4992, SciTePress, pages 87-92. DOI: 10.5220/0003952800870092

@conference{iceis12,
author={Andrzej Wichert.},
title={Product Quantization for Vector Retrieval with No Error},
booktitle={Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2012},
pages={87-92},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003952800870092},
isbn={978-989-8565-10-5},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Product Quantization for Vector Retrieval with No Error
SN - 978-989-8565-10-5
IS - 2184-4992
AU - Wichert, A.
PY - 2012
SP - 87
EP - 92
DO - 10.5220/0003952800870092
PB - SciTePress

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