Simple and Efficient Algorithm for Approximate Dictionary Matching

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 similarity and threshold 0.7).