Neighborhood preserving hashing and approximate queries

Let D ⊆ ∑ⁿ be a dictionary. We look for efficient data structures and algorithms to solve the following approximate query problem: Given a query u ∈ ∑ⁿ list all words v ∈ D that are close to u in Hamming distance. The problem reduces to the following combinatorial problem: Hash the vertices of the n-dimensional hypercube into buckets so that (1) the c-neighborhood of each vertex is mapped into at most k buckets and (2) no bucket is too large. Lower and upper bounds are given for the tradeoff between k and the size of the largest bucket. These results are used to derive bounds for the approximate query problem.