
Approximating Edit Distance Within Constant Factor in Truly SubQuadratic Time
Edit distance is a measure of similarity of two strings based on the min...
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Convolutional Embedding for Edit Distance
Editdistancebased string similarity search has many applications such ...
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MinJoin: Efficient Edit Similarity Joins via Local Hash Minimums
In this paper we study edit similarity joins, in which we are given a se...
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Analyzing Walter Skeat's FortyFive Parallel Extracts of William Langland's Piers Plowman
Walter Skeat published his critical edition of William Langland's 14th c...
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Edit Distance Embedding using Convolutional Neural Networks
Editdistancebased string similarity search has many applications such ...
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TrQuery: An Embeddingbased Framework for Recommanding SPARQL Queries
In this paper, we present an embeddingbased framework (TrQuery) for rec...
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An Almost Optimal Edit Distance Oracle
We consider the problem of preprocessing two strings S and T, of lengths...
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Approximate Similarity Search Under Edit Distance Using LocalitySensitive Hashing
Edit distance similarity search, also called approximate pattern matching, is a fundamental problem with widespread applications. The goal of the problem is to preprocess n strings of length d to quickly answer queries q of the form: if there is a database string within edit distance r of q, return a database string within edit distance cr of q. A data structure solving this problem is analyzed using two criteria: the amount of extra space used in preprocessing, and the expected time to answer a query. Previous approaches to this problem have either used triebased methods, which give exact solutions at the cost of expensive queries, or embeddings, which only work for large (superconstant) values of c. In this work we achieve the first bounds for any approximation factor c, via a simple and easytoimplement hash function. This gives a running time of Õ(d3^rn^1/c), with space Õ(3^r n^1 + 1/c + dn). We show how to apply these ideas to the closelyrelated Approximate Nearest Neighbor problem for edit distance, obtaining similar time bounds.
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