Research Online

Logo

Goldsmiths - University of London

Sparse p-Adic Data Coding for Computationally Efficient and Effective Big Data Analytics

Murtagh, Fionn. 2016. Sparse p-Adic Data Coding for Computationally Efficient and Effective Big Data Analytics. Journal of p-Adic Numbers, Ultrametric Analysis and Applications, 8(3), pp. 236-247. ISSN 2070-0466 [Article]

[img]
Preview
Text (Sparse p-Adic Data Coding for Computationally Efficient and Effective Big Data Analytics)
1604.06961v1.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (928kB) | Preview

Abstract or Description

We develop the theory and practical implementation of p-adic sparse coding of data. Rather than the standard, sparsifying criterion that uses the $L_0$ pseudo-norm, we use the p-adic
norm.We require that the hierarchy or tree be node-ranked, as is standard practice in agglomerative and other hierarchical clustering, but not necessarily with decision trees. In order to structure the data, all computational processing operations are direct reading of the data, or are bounded by a constant number of direct readings of the data, implying linear computational time. Through p-adic sparse data coding, efficient storage results, and for bounded p-adic norm stored data, search and retrieval are constant time operations. Examples show the effectiveness of this new approach to content-driven encoding and displaying of data.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.1134/S2070046616030055

Keywords:

big data, p-adic numbers, ultrametric topology, hierarchical clustering, binary rooted tree, computational and storage complexity

Related URLs:

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
24 August 2016Published
17 June 2016Accepted

Item ID:

18816

Date Deposited:

18 Aug 2016 07:05

Last Modified:

10 Jul 2018 06:55

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

http://research.gold.ac.uk/id/eprint/18816

View statistics for this item...

Edit Record Edit Record (login required)