Você tem que decidir que método de similaridade de Strings você vai usar.
Eis alguns deles:
In information theory and computer science, the Damerau–Levenshtein distance (named after Frederick J. Damerau and Vladimir I. Levenshtein) is a string metric for measuring the edit distance between two sequences. Informally, the Damerau–Levenshtein distance between two words is the minimum number of operations (consisting of insertions, deletions or substitutions of a single character, or transposition of two adjacent characters) required to change one word into the other.
The Damerau–Levenshte...
The Sørensen–Dice coefficient (see below for other names) is a statistic used to gauge the similarity of two samples. It was independently developed by the botanists Thorvald Sørensen and Lee Raymond Dice, who published in 1948 and 1945 respectively.
The index is known by several other names, especially Sørensen–Dice index, Sørensen index and Dice's coefficient. Other variations include the "similarity coefficient" or "index", such as Dice similarity coefficient (DSC). Common alternate spellings...
In information theory, linguistics and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. Informally, the Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. It is named after the Soviet mathematician Vladimir Levenshtein, who considered this distance in 1965.
Levenshtein distance may also be referred to as edit dis...
Essa página também lista vários deles:http://www.dcs.shef.ac.uk/~sam/stringmetrics.html
E o pessoal do link acima fez essa biblioteca (caso você mesmo não precise implementar a solução):
Download SimMetrics for free. SimMetrics is a Similarity Metric Library, e.g. from edit distance's (Levenshtein, Gotoh, Jaro etc) to other metrics, (e.g Soundex, Chapman).
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