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.
Originalsprog | Engelsk |
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Tidsskrift | CEUR Workshop Proceedings |
Vol/bind | 1624 |
Sider (fra-til) | 363-376 |
Antal sider | 14 |
ISSN | 1613-0073 |
Status | Udgivet - 15 jul. 2016 |
Emneord
- Formal Concept Analysis
- Knowledge Discovery
- Conceptual Neighbourhoods
- FCbO Update Algorithm
- Scalability Limitations