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Automatically building a large bilingual corpus that contains millions of words is always a challenging task. In particular in case of low-resource languages, it is difficult to find an existing parallel corpus which is large enough for building a real statistical machine translation. However, comparable non-parallel corpora are richly available in the Internet environment, such as in Wikipedia, and from which we can extract valuable parallel texts. This work presents a framework for effectively extracting parallel sentences from that resource, which results in significantly improving the performance of statistical machine translation systems. Our framework is a bootstrapping-based method that is strengthened by using a new measurement for estimating the similarity between two bilingual sentences. We conduct experiment for the language pair of English and Vietnamese and obtain promising results on both constructing parallel corpora and improving the accuracy of machine translation from English to Vietnamese.
Content available CardS4: modal theorem proving on Java smart cards
We describe a successful implementation of a theorem prover for modal logic S4 that runs on a Java smart card with only 512 KBytes of RAM and 32 KBytes of EEPROM. Since proof search in S4 can lead to infinite branches, this is "proof of principle" that non-trivial modal deduction is feasible even on current Java cards. We hope to use this prover as the basis of an on-board security manager for restricting the flow of "secrets" between multiple applets residing on the same card, although much work needs to be done to design the appropriate modal logics of "permission" and "obligations". Such security concerns are the major impediments to the commercial deployment of multi-application smart cards.
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