Similarity join is a key operation in metric databases. It retrieves all pairs of elements that are similar. Solving such a problem usually requires comparing every pair of objects of the datasets, even when indexing and ...

We introduce an approximate analytic solution for the S=1/2 one-dimensional antiferromagnetic Heisenberg model with coupling between nearest- and next-nearest-neighbor spins. Closed-form expressions for the ground state, ...

Proximity searching is the problem of retrieving,from a given database, those objects closest to a query.To avoid exhaustive searching,data structures called indexes are builton the database prior to serving queries.The ...

The k-Nearest Neighbor query (k-NNq) is one of the most useful similarity queries. Elaborated k-NNq algorithms depend on an initial radius to prune regions of the search space that cannot contribute to the answer. Therefore, ...

The use of the join operator in metric spaces leads to what is known as a similarity join, where objects of two datasets are paired if they are somehow similar. We propose an heuristic that solves the 1-NN selfsimilarity ...