| 1. |
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Levenshtein Distance
- Levenshtein distance (LD) is a measure of the similarity between two strings, which we will refer to as the source
string (s) and the target string (t). The distance is the number of deletions, insertions, or substitutions required to
transform s into t.
URL: http://www.merriampark.com/ld.htm
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| 2. |
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Dynamic Programming Algorithm (DPA) for Edit-Distance
- The words `computer' and `commuter' are very similar, and a change of just one
letter, p->m will change the first word into the second. The word `sport' can be
changed into `sort' by the deletion of the `p', or equivalently, `sort' can be changed
into `sport' by the insertion of `p'.
URL: http://www.csse.monash.edu.au/~lloyd/tildeAlgDS/Dynamic/Edit/
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| 3. |
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A versatile divide and conquer technique for optimal string alignment
- Common string alignment algorithms such as the dynamic
programming algorithm (DPA) and the time efficient Ukkonen
algorithm use quadratic space to determine an alignment between
two strings. In this paper we present a technique that can be
applied to these algorithms to obtain an alignment using only
linear space, while having little or no effect on the time
complexity.
URL: http://www.csse.monash.edu.au/~lloyd/tildeStrings/Alignment/1999IPLa.html
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| 4. |
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Levenshtein 0.8
- Levenshtein is a Python C extension and C libray to compute Levenshtein
string distance, string similarity, normal and generalized string set medians,
and other related quantities.
URL: http://freshmeat.net/projects/levenshtein/?branch_id=38711&release_id=122409&topic_id=97%2C809%2C912%2C849
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