Scalable Performance of FCbO Algorithm on Museum Data

Tim Wray, Jan Outrata, Peter Eklund

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Abstract

Formal Concept Analysis – known as a technique for data analysis and visualisation – can also be applied as a means of creating interaction approaches that allow for knowledge discovery within collec- tions of content. These interaction approaches rely on performant algo- rithms that can generate conceptual neighbourhoods based on a single formal concept, or incrementally compute and update a set of formal concepts given changes to a formal context. Using case studies based on content from museum collections, this paper describes the scalabil- ity limitations of existing interaction approaches and presents an imple- mentation and evaluation of the FCbO update algorithm as a means of updating formal concepts from large and dynamically changing museum datasets.
OriginalsprogEngelsk
TidsskriftCEUR Workshop Proceedings
Vol/bind1624
Sider (fra-til)363-376
Antal sider14
ISSN1613-0073
StatusUdgivet - 15 jul. 2016

Emneord

  • Formal Concept Analysis
  • Knowledge Discovery
  • Conceptual Neighbourhoods
  • FCbO Update Algorithm
  • Scalability Limitations

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