loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Jaime Salvador-Meneses 1 ; Zoila Ruiz-Chavez 1 and Jose Garcia-Rodriguez 2

Affiliations: 1 Universidad Central del Ecuador, Ciudadela Universitaria, Quito and Ecuador ; 2 Universidad de Alicante, Ap. 99. 03080, Alicante and Spain

Keyword(s): Big Data, Compression, Processing, Categorical Data, BLAS.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Data Reduction and Quality Assessment ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Pre-Processing and Post-Processing for Data Mining ; Soft Computing ; Symbolic Systems

Abstract: The machine learning algorithms, prior to their application, require that the information be stored in memory. Reducing the amount of memory used for data representation clearly reduces the number of operations required to process it. Many of the current libraries represent the information in the traditional way, which forces you to iterate the whole set of data to obtain the desired result. In this paper we propose a technique to process categorical information previously encoded using the bit-level schema, the method proposes a block processing which reduces the number of iterations on the original data and, at the same time, maintains a processing performance similar to the processing of the original data. The method requires the information to be stored in memory, which allows you to optimize the volume of memory consumed for representation as well as the operations required to process it. The results of the experiments carried out show a slightly lower time processing than the o btained with traditional implementations, which allows us to obtain a good performance. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 174.129.59.198

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Salvador-Meneses, J.; Ruiz-Chavez, Z. and Garcia-Rodriguez, J. (2018). Low Level Big Data Processing. In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KDIR; ISBN 978-989-758-330-8; ISSN 2184-3228, SciTePress, pages 347-352. DOI: 10.5220/0007227103470352

@conference{kdir18,
author={Jaime Salvador{-}Meneses. and Zoila Ruiz{-}Chavez. and Jose Garcia{-}Rodriguez.},
title={Low Level Big Data Processing},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KDIR},
year={2018},
pages={347-352},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007227103470352},
isbn={978-989-758-330-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KDIR
TI - Low Level Big Data Processing
SN - 978-989-758-330-8
IS - 2184-3228
AU - Salvador-Meneses, J.
AU - Ruiz-Chavez, Z.
AU - Garcia-Rodriguez, J.
PY - 2018
SP - 347
EP - 352
DO - 10.5220/0007227103470352
PB - SciTePress