| Summary: | 碩士 === 國立交通大學 === 資訊工程系 === 89 === With the rapid development of information technologies, the way
people store, present, process and exchange data have been
changed. More and more documents, including videos and audio, are
store in digital formats now. The population of internet also
increases the frequency of using searching systems to find
information we want. The new types of information retrieval
systems, especially multi-media query systems, must use more
efficient automatic techniques to provide easy and effective
retrieval service.
In this thesis, a method is proposed which utilize current text
information processing techniques for news video classification.
The goal is to build a system which effectively analysis news
videos and further classify them into some previously defined
categories. The method proposed use recent probabilistic based
text classifying algorithms associate with optical character
recognition techniques. Experimental results show that this method
can achieve good classification performance under real conditions
using daily TV news.
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