Searching by approximate personal-name matching

We discuss the design, building and evaluation of a method to access theinformation of a person, using his name as a search key, even if it has deformations. We present a similarity function, the DEA function, based on the probabilities of the edit operations accordingly to the involved letters and their position, and using a variable threshold. The efficacy of DEA is quantitatively evaluated, without human relevance judgments, very superior to the efficacy of known methods. A very efficient approximate search technique for the DEA function is also presented based on a compacted trie-tree structure.Postprint (published version

Fast Approximate Reconciliation of Set Differences

We present new, simple, efficient data structures for approximate reconciliation of set differences, a useful standalone primitive for peer-to-peer networks and a natural subroutine in methods for exact reconciliation. In the approximate reconciliation problem, peers A and B respectively have subsets of elements SA and SB of a large universe U. Peer A wishes to send a short message M to peer B with the goal that B should use M to determine as many elements in the set SB–SA as possible. To avoid the expense of round trip communication times, we focus on the situation where a single message M is sent. We motivate the performance tradeoffs between message size, accuracy and computation time for this problem with a straightforward approach using Bloom filters. We then introduce approximation reconciliation trees, a more computationally efficient solution that combines techniques from Patricia tries, Merkle trees, and Bloom filters. We present an analysis of approximation reconciliation trees and provide experimental results comparing the various methods proposed for approximate reconciliation.National Science Foundation (ANI-0093296, ANI-9986397, CCR-0118701, CCR-0121154); Alfred P. Sloan Research Fellowshi

Lattice template placement for coherent all-sky searches for gravitational-wave pulsars

All-sky, broadband, coherent searches for gravitational-wave pulsars are restricted by limited computational resources. Minimizing the number of templates required to cover the search parameter space, of sky position and frequency evolution, is one important way to reduce the computational cost of a search. We demonstrate a practical algorithm which, for the first time, achieves template placement with a minimal number of templates for an all-sky search, using the reduced supersky parameter-space metric of Wette and Prix [Phys. Rev. D 88, 123005 (2013)]. The metric prescribes a constant template density in the signal parameters, which permits that templates be placed at the vertices of a lattice. We demonstrate how to ensure complete coverage of the parameter space, including in particular at its boundaries. The number of templates generated by the algorithm is compared to theoretical estimates, and to previous predictions by Brady et al. [Phys. Rev. D 57, 2101 (1998)]. The algorithm may be applied to any search parameter space with a constant template density, which includes semicoherent searches and searches targeting known low-mass X-ray binaries.Comment: 16 pages, 14 figure