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 text using 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.

• Type: Journal
• Year: 2009
• Where: ICDAR
• Authors: Atsuhiro Takasu
• Keywords: Approximate String Search, Approximate Text Search, Document Analysis, ICDAR 2009, Parameter Estimation