A Set Of Applied To Text Information Hiding Analysis Algorithm Design And Implementation

With the wide application and in-depth research of natural language information hiding technology, hidden capacity and concealment of text information hiding became the main problems. Not only some higher requirements for the hiding algorithm was caused by these problems, but also some greater challenges to the identification of natural language, which, in this case, needs analysis on grammar and syntax and analysis on the semantics and pragmatics of natural language.This paper researches on the technique which identifies the natural language in natural language information hidden text carrier. With learning and study of natural language processing, computational linguistics and natural language recognition technology, we propose a method based on combining statistical and rule of natural language chunking. Bottom-up chunk of analysis algorithms in this method not only analyzes the grammar and syntax of natural language, but also analyzes semantics and pragmatics of natural language. For the analysis of large natural language corpus, the work efficiency of chunking method proposed in this paper is treated as important research content. With the experiment, the efficiency of this method was proved to be improved greatly.Finally, this study designed and implemented a prototype system with a multi-step integration of bottom-up group block analysis algorithm. Functionally, this prototype system is divided into two major parts:SVM initial chunking and chunking from the bottom-up chunking algorithm. The experiments show that the multi-step integration of bottom-up chunking method proposed in this paper could not only identify grammar and syntax information better, but also identify semantics and pragmatics of natural language recognition with higher precision and recall rate, at the same time, the system also has a good working efficiency.