1. A method of learning user query concept for searching objects encoded in computer readable storage media comprising: providing a multiplicity of respective sample objects encoded in a computer readable medium; providing a multiplicity of respective sample expressions encoded in computer readable medium that respectively correspond to respective sample objects and in which respective predicates of such respective sample expressions represent respective features of corresponding sample objects; defining a user query concept sample space bounded by a boundary k-CNF expression which designates a more specific concept within the user query concept sample space and by a boundary k-DNF expression which designates a more general concept within the user query concept sample space; refining the user query concept sample space by, selecting multiple sample objects from within the user query concept sample space; presenting the multiple selected sample objects to the user; soliciting user feedback as to closeness of individual ones of the multiple presented sample objects to the user's query concept; wherein refining the user query concept sample space further includes refining the boundary k-CNF expression by identifying respective predicates of respective sample expressions that are different from corresponding respective predicates of the boundary k-CNF expression for those respective sample expressions corresponding to respective sample objects indicated by the user as close to the user's query concept; determining which, if any, respective predicates of the boundary k-CNF expression identified as different from corresponding respective predicates of sample expressions indicated by the user as close to the user's query concept to remove from the boundary k-CNF expression; removing from the boundary k-CNF expression respective predicates determined to be removed; wherein refining the user query concept sample space further includes, refining the boundary k-DNF expression by, identifying respective predicates of respective sample expressions that are not different from corresponding respective predicates of the boundary k-DNF expression for those respective sample expressions corresponding to respective sample objects indicated by the user as not close to the user's query concept; determining which, if any, respective predicates of the boundary k-DNF expression-identified as not different from corresponding respective predicates of sample expressions indicated by the user as not close to the user's query concept to remove from the boundary k-DNF expression; and removing from the boundary k-DNF expression respective predicates determined to be removed.