Algorithme de recherche approximative dans un dictionnaire fond\'e sur une distance d'\'edition d\'efinie par blocs

TL;DR

The paper introduces an approximate string matching algorithm for dictionaries that uses a customizable divergence function based on block character costs, improving flexibility over classical edit distances.

Contribution

It presents a novel approximate string search algorithm utilizing a block-based divergence function tailored to specific corpora, enhancing matching accuracy.

Findings

The algorithm effectively matches altered strings within a threshold.

It adapts to different corpora through customizable block costs.

Performance surpasses traditional character-based edit distances.

Abstract

We propose an algorithm for approximative dictionary lookup, where altered strings are matched against reference forms. The algorithm makes use of a divergence function between strings -- broadly belonging to the family of edit distances; it finds dictionary entries whose distance to the search string is below a certain threshold. The divergence function is not the classical edit distance (DL distance); it is adaptable to a particular corpus, and is based on elementary alteration costs defined on character blocks, rather than on individual characters. Nous proposons un algorithme de recherche approximative de cha\^ines dans un dictionnaire \`a partir de formes alt\'er\'ees. Cet algorithme est fond\'e sur une fonction de divergence entre cha\^ines~ -- une sorte de distance d'\'edition: il recherche des entr\'ees pour lesquelles la distance \`a la cha\^ine cherch\'ee est inf\'erieure \`a un certain seuil. La fonction utilis\'ee n'est pas la distance d'\'edition classique (distance DL); elle est adapt\'ee \`a un corpus, et se fonde sur la prise en compte de co\^uts d'alt\'eration \'el\'ementaires d\'efinis non pas sur des caract\`eres, mais sur des sous-cha\^ines (des blocs de caract\`eres).