Scalable Performance of FCbO Algorithm on Museum Data

Tim Wray, Jan Outrata, Peter Eklund

Research output: Journal Article or Conference Article in JournalConference articleResearchpeer-review


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.
Original languageEnglish
JournalCEUR Workshop Proceedings
Pages (from-to)363-376
Number of pages14
Publication statusPublished - 15 Jul 2016


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


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