Formal Concept Analysis With Background Knowledge: Attribute Priorities.

The article presents a study on the model background in knowledge extraction from binary data. It highlights the importance of background knowledge in giving additional information to the user. It notes on the proposed approach of the modeling background knowledge which represent the user's priorities regarding attributes and its relative importance. It notes on the two main practical features of the approach which are constantly used in the knowledge extraction and emphasizes on the fundamental aspects of mathematical feasibility, reasoning with background knowledge, and the removal of redundancy.