Self-Organizing Maps for Data Purchase Support in Data Marketplaces

Martins, Denis Mayr Lima; Vossen, Gottfried


Abstract

Data marketplaces have become popular in recent years, in particular for enterprises who want to enrich their own data with novel data from outside in order to improve their decision-making. A data marketplace is a platform that brings data producers and data consumers together; the platform itself provides the necessary infrastructure. Since producers want to maximize their revenue, while consumers want to minimize their spending, data pricing is among the central problems for a data marketplace. This paper investigates an approach in which the amount of data purchased is potentially minimized due to an indication of redundancy within the data or similarities between parts of the data. Thus, it is difficult for a buyer to decide whether all or just parts of the data should be paid for. The approach described utilizes Self-Organizing Maps and shows how they can be used to support a purchase decision.

Keywords
self-organizing maps, data marketplace



Publication type
Research article in proceedings (conference)

Peer reviewed
Yes

Publication status
Published

Year
2023

Conference
15th International Conference on Computational Collective Intelligence (ICCCI)

Venue
Budapest

Volume
14162

Book title
Computational Collective Intelligence

Editor
Ngoc Thanh Nguyen, János Botzheim, László Gulyás, Manuel Núñez, Jan Treur, Gottfried Vossen, Adrianna Kozierkiewicz

Start page
43

End page
55

Volume
14162

Title of series
Lecture Notes in Computer Science

Publisher
Springer International Publishing

Place
Heidelberg

Language
English

ISSN
0302-9743

ISBN
978-3-031-41455-8

DOI