Information Extraction by Two Dimensional Parser

This paper proposes a learning algorithm for a two dimensional parser. The parser is designed to analyze page layout of documents and extract information using both textual and layout information. The parsing rules are expressed by an extended stochastic context free grammar that decomposes tokens located in two dimensional space both horizontally and vertically. In this paper we focus on the learning aspect of the parser and propose a learning algorithm based on the expectation maximization technique where the dynamic programming (DP) technique is used for efficient process. We apply the proposed algorithm to acquire a stochastic parser for information extraction from scanned document images and show that learned stochastic grammar extracts bibliographic data with high accuracy.