Approximate String Matching Using Markovian Distance
A Katsumata, T Miura, Isamu Shioya · 2010
In this work we examine a new technique for approximate string matching using Markovian distance. Here we assume each character appears in a probabilistic way. By means of this idea, we introduce a notion of dissimilarity using text corpus. Then we propose our sophisticated algorithm based on dynamic programming. We show some experimental results to see how the approach works well.