Retraction Note: Non-point source pollution in river basin based on Bayesian network and intelligent translation system of English books

With the rapid development of social science and industrial technology, more attention has been paid to evaluation water environmental pollution. Bayesian network strong probability theory inference ability, clear semantics, easy understand, other technical characteristics. This provides a natural effective way express dependency causality, which can find potential relationships patterns in datasets. Therefore, it its own advantages data mining. technology is used study non-point source pollution river basin intelligent translation system English books. Water one main problems that human beings are facing. In China, serious. First all, acceleration urbanization change land use will lead surface vegetation, resulting loss soil water. Secondly, many fertilizers, pesticides, chemical reagents agricultural activities, some absorbed by crops, most rest released from process rainfall. “Machine + post-translation editing” mode widely various projects, Chinese subtitle project “a little English” learning software adopted this mode. practice, found “machine post-editing improve efficiency E-C translation, but there also limitations. paper, analyzing cases English-Chinese software, typical errors machine summarized, corresponding editing strategies proposed for different error types. The at lexical level wrong choice word meaning, no abbreviations, coined words. locate polysemous