Formal concept analysis is a method of exploratory data analysisthat aims at the extraction of natural cluster from object-attributedata tables. We present a way to add user's background knowledge toformal concept analysis. The type of background knowledge we dealwith relates to relative importance of attributes in the input data.We introduce EM operators which constrain in attributes of formalconcept analysis. The main aim is to make extraction of conceptsfrom the input data more focused by taking into account thebackground knowledge. Particularly, only concepts which arecompatible with the constraint are extracted from data. Therefore,the number of extracted concepts becomes smaller since we leave outnon-interesting concepts. We concentrate on foundational aspectssuch as mathematical feasibility and computational tractability.