A method of mining bilingual resources from Web Based on Maximum Frequent Sequential Pattern

Abstract

The bilingual resources are indispensable and vital resources in the NPL fields, such as machine translation, etc. A large amount of electronic information is embedded in the Internet, which can be used as a potential information source of large-scale multi-language corpus, so it is a potential and feasible way to mine a great capacity of true bilingual resources from the Web. This paper proposes a method of mining bilingual resources from the Web based on Maximum Frequent Sequential Pattern. The method uses the heuristic approach to search and filter the candidate bilingual web pages, then mines patterns using maximum frequent sequential, and uses a machine learning method for extending the pattern base and verifying bilingual resources in accordance with the Japanese to Chinese word proportion. The experimental results indicate that the method could extract bilingual resources efficiently, with the precision rate over 90%.