Therefore in this paper, we propose a pattern-based approach: learning patterns adaptively from collective bilingual pages instead of using the parenthesis pattern, then using the learned patterns to extract translation pairs from corresponding web pages.
our approach contains four steps: 1) Preprocessing: parse the web page into a DOM tree and segment the inner text of each node into snippets; 2) Seed mining: identify potential translation pairs (seeds) using an alignment model which takes both translation and transliteration into consideration; 3) Pattern learning: learn generalized patterns with the identified seeds; 4) Pattern based mining: extract all bilingual data in the page using the learnt patterns.