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Author: Been-Chian Chien

Affiliation: National University of Tainan, Taiwan

ISBN: 978-989-758-035-2

Keyword(s): High-dimensional Data, Data Reduction, Feature Selection, Clustering, Document Categorization.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Dimensional Modeling ; Enterprise Information Systems ; Health Information Systems ; Information Retrieval ; Ontologies and the Semantic Web ; Pattern Recognition ; Sensor Networks ; Signal Processing ; Soft Computing ; Software Engineering

Abstract: Data reduction is an important research topic for analyzing mass data efficiently and effectively in the era of big data. The task of dimension reduction is usually accomplished by technologies of feature selection, feature clustering or algebraic transformation. A novel approach for reducing high-dimensional data is initiated in this paper. The main idea of the proposed scheme is to incorporate data clustering and feature selection to transform high-dimensional data into lower dimensions. The incremental clustering algorithm in the scheme is used to handle the number of dimensions, and the relative discriminant variable is design for selecting significant features. Finally, a simple inner product operation is applied to transform original highdimensional data into a low one. Evaluations are conducted by testing the reduction approach on the problem of document categorization. The experimental results show that the reduced data have high classification accuracy for most of datasets. F or some special datasets, the reduced data can get higher classification accuracy in comparison with original data. (More)

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Paper citation in several formats:
Chien, B. (2014). Incorporating Feature Selection and Clustering Approaches for High-Dimensional Data Reduction.In Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA, ISBN 978-989-758-035-2, pages 72-77. DOI: 10.5220/0005093300720077

@conference{data14,
author={Been{-}Chian Chien.},
title={Incorporating Feature Selection and Clustering Approaches for High-Dimensional Data Reduction},
booktitle={Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA,},
year={2014},
pages={72-77},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005093300720077},
isbn={978-989-758-035-2},
}

TY - CONF

JO - Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA,
TI - Incorporating Feature Selection and Clustering Approaches for High-Dimensional Data Reduction
SN - 978-989-758-035-2
AU - Chien, B.
PY - 2014
SP - 72
EP - 77
DO - 10.5220/0005093300720077

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