Knowledge Graph Alignment using String Edit Distance

03/13/2020

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In this work, we propose a novel knowledge base alignment technique based upon string edit distance that exploits the type information about entities and can can find similarity between relations of any arity

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Knowledge Graph Alignment using String Edit Distance

Algorithm to derive shortest edit script using Levenshtein distance algorithm

Neural String Edit Distance

Edit Distance Embedding using Convolutional Neural Networks

string2string: A Modern Python Library for String-to-String Algorithms

Analyzing Walter Skeat's Forty-Five Parallel Extracts of William Langland's Piers Plowman

Scalable Alignment Kernels via Space-Efficient Feature Maps

String Sanitization Under Edit Distance: Improved and Generalized

Knowledge Graph Alignment using String Edit Distance

Related Research

Algorithm to derive shortest edit script using Levenshtein distance algorithm

Neural String Edit Distance

Edit Distance Embedding using Convolutional Neural Networks

string2string: A Modern Python Library for String-to-String Algorithms

Analyzing Walter Skeat's Forty-Five Parallel Extracts of William Langland's Piers Plowman

Scalable Alignment Kernels via Space-Efficient Feature Maps

String Sanitization Under Edit Distance: Improved and Generalized