Phonetic matching is used in applications such as name retrieval, where the spelling of a name is used to identify other strings that are likely to be of similar pronunciation. In this paper we explain the parallels between information retrieval and phonetic matching, and describe our new phonetic matching techniques. Our experimental comparison with existing techniques such as Soundex and edit distances, which is based on recall and precision, demonstrates that the new techniques are superior. In addition, reasoning from the similarity of phonetic matching and information retrieval, we have applied combination of evidence to phonetic matching. Our experiments with combining demonstrate that it leads to substantial improvements in effectiveness.

Approximate string matching is used for spelling correction and personal name matching. In this paper we show how to use string matching techniques in conjunction with lexicon indexes to find approximate matches in a large lexicon. We test several lexicon indexing techniques, including n-grams and permuted lexicons, and several string matching techniques, including string similarity measures and phonetic coding. We propose methods for combining these techniques, and show experimentally that these combinations yield good retrieval effectiveness while keeping index size and retrieval time low. Our experiments also suggest that, in contrast to previous claims, phonetic codings are markedly inferior to string distance measures, which are demonstrated to be suitable for both spelling correction and personal name matching. KEY WORDS: pattern matching; string indexing; approximate matching; compressed inverted files; Soundex

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This paper describes ETK (Ensemble of Transformation based Keys) a new algorithm for inducing search keys for name filtering. ETK has the low computational cost and ability to filter by phonetic similarity characteristic of phonetic keys but is adaptable to alternative similarity models. A preliminary empirical evaluation suggests that ETK may be well-suited for phonetic filtering applications such as recognizing alternative cross-lingual transliterations. 1 1