Knowledge Discovery in Databases Using Formal Concept Analysis
โ Scribed by Uta Priss
- Publisher
- American Society for Information Science and Technology
- Year
- 2005
- Tongue
- English
- Weight
- 657 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0095-4403
- DOI
- 10.1002/bult.186
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Modern database technologies process large volumes of data to discover new knowledge. Some large databases make discovery computationally expensive. Additional knowledge, known as domain or background knowledge, can often guide and restrict the search for interesting knowledge. This paper discusses
Digital obesity, or information overload, is a widely recognized yet largely unsolved problem. Lack of metadata-that is, a useful and usable description of what is represented by data-is one of the fundamental obstacles preventing the wider use of computational intelligence techniques in tackling th
This paper uses the techniques of knowledge discovery in databases (KDD) and data visualization as a methodology to uncover significant clusters in the ownership of risky financial assets. Partitioning by medoids and data visualization identifies two significant clusters among risky asset holders. C
In recent years there has been growing interest in supporting knowledge discovery activities using map-based visual interfaces. The goal is promising and ambitious, but not very easy to achieve due to the lack of understanding of cognitive factors involved in how information is transformed into know