SNN Input Parameters: how are they related?

Guilherme Moreira, Maribel Yasmina Santos, Joao Moura-Pires

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Citations (Scopus)

Abstract

Nowadays, organizations are facing several challenges when they try to analyze generated data with the aim of extracting useful information. This analytical capacity needs to be enhanced with tools capable of dealing with big data sets without making the analytical process a difficult task. Clustering is usually used, as this technique does not require any prior knowledge about the data. However, clustering algorithms usually require one or more input parameters that influence the clustering process and the results that can be obtained. This work analyses the relation between the three input parameters of the SNN (Shared Nearest Neighbor) algorithm and proposes specific guidelines for the identification of the appropriate input parameters that optimizes the processing time.

Original languageEnglish
Title of host publication2013 19TH IEEE INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS (ICPADS 2013)
PublisherIEEE
Pages492-497
Number of pages6
DOIs
Publication statusPublished - 2013
Event19th IEEE International Conference on Parallel and Distributed Systems (ICPADS) - Seoul
Duration: 15 Dec 201318 Dec 2013

Publication series

NameInternational Conference on Parallel and Distributed Systems - Proceedings
PublisherIEEE
ISSN (Print)1521-9097

Conference

Conference19th IEEE International Conference on Parallel and Distributed Systems (ICPADS)
CitySeoul
Period15/12/1318/12/13

Keywords

  • clustering
  • density-based clustering
  • shared nearest neighbor
  • input parameters tuning

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