Bayesian Similarity Model Estimation for Approximate Recognized Text Search

Approximate text search is a basic technique to handle recognized text that contains recognition errors. This paper proposes an approximate string search for recognized texturing a statistical similarity model focusing on parameter estimation. The main contribution of this paper is to propose a parameter estimation algorithm using variational Bayesian expectation maximization technique. We applied the obtained model to approximate substring detection problem and experimentally showed that the Bayesian estimation is effective.