Using Hidden Markov Model for Identifying Secure Text of Public Opinion Based on Maximum Entropy

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Provided by: Binary Information Press
Topic: Security
Format: PDF
With wide spreading of network and quick developing of E-commerce, on-line reviews and news group discussions have become important parts in people's daily life. How to identify the semantic orientation of these reviews on sensitive topics, such as Taiwan independence and Falun Gong, and how to effectively control the public opinions and feelings on Internet, have been a focus for the research of information security. This paper presents a Hidden Markov Model Based on Maximum Entropy, for identifying the rules of integrating with statistics on the network security text.
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