Learning from ubiquitous data streams: Clustering data and data sources

• Type: Article in International Scientific Journal
• Date: 2012

Authors

Pedro Pereira Rodrigues (Author) FMUP

Journal

Title: AI Communications

Vol. 25

Pages: 69-71

ISSN: 0921-7126

Publisher: IOS PRESS

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-002-GV7

DOI: 10.3233/aic-2011-0510

Abstract (EN): Knowledge discovery techniques try to extract patterns and concepts from raw data, and clustering certainly is one of the most popular processes in this research field. However, nowadays data is being produced in streaming fashion and distributed locations, turning most classical methods obsolete. This thesis addresses two different clustering problems in ubiquitous and streaming scenarios, presenting evidence of the advantages produced by applying distributed and streaming machine learning algorithms, and proposing new ones to solve the addressed problems.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 3