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Bernard Brenyah edited this page Feb 10, 2022
·
1 revision
This paper presents a simple and efficient algorithm for approximate dictionary matching designed for similarity
measures such as cosine, Dice, Jaccard,
and overlap coefficients. We propose this
algorithm, called CPMerge, for the τ -
overlap join of inverted lists. First we
show that this task is solvable exactly by
a τ -overlap join. Given inverted lists retrieved for a query, the algorithm collects
fewer candidate strings and prunes unlikely candidates to efficiently find strings
that satisfy the constraint of the τ -overlap
join. We conducted experiments of approximate dictionary matching on three
large-scale datasets that include person
names, biomedical names, and general
English words. The algorithm exhibited scalable performance on the datasets.
For example, it retrieved strings in 1.1
ms from the string collection of Google
Web1T unigrams (with cosine)