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Towards Distributed k-NN similarity for Scalable Case Retrieval
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-7305-7169
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1212-7637
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-3802-4721
2018 (English)In: ICCBR 2018: The 26th International Conference on Case-Based Reasoning July, 09th-12th 2018 in Stockholm, Sweden, Workshop Proceedings, 2018, p. 151-160Conference paper, Published paper (Refereed)
Abstract [en]

In Big data era, the demand of processing large amount of data posing several challenges. One biggest challenge is that it is no longer possible to process the data in a single machine. Similar challenges can be assumed for case-based reasoning (CBR) approach, where the size of a case library is increasing and constructed using heterogenous data sources. To deal with the challenges of big data in CBR, a distributed CBR system can be developed, where case libraries or cases are distributed over clusters. MapReduce programming framework has the facilities of parallel processing massive amount of data through a distributed system. This paper proposes a scalable case-representation and retrieval approach using distributed k-NN similarity. The proposed approach is considered to be developed using MapReduce programming framework, where cases are distributed in many clusters.

Place, publisher, year, edition, pages
2018. p. 151-160
Keywords [en]
Case representation, k-NN similarity, Scalable Case Retrieval, distributed CBR, big data
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-40882OAI: oai:DiVA.org:mdh-40882DiVA, id: diva2:1249199
Conference
XCBR: First Workshop on Case-Based Reasoning for the Explanation of Intelligent Systems. Workshop at the 26th International Conference on Case-Based Reasoning (ICCBR 2018)
Available from: 2018-09-18 Created: 2018-09-18 Last updated: 2018-09-18Bibliographically approved

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http://iccbr18.com/wp-content/uploads/ICCBR-2018-V3.pdf

Authority records BETA

Barua, ShaibalBegum, ShahinaAhmed, Mobyen Uddin

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf