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A Method of Behavior Evaluation Based on Web Browsing Information

机译:一种基于Web浏览信息的行为评估方法

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In order to improve the value of web browsing history data and evaluate peoples web browsing behavior, a method for browsing history data based on TF-IDF and Naive Bayes which is used to classify peoples behavior on the Internet is designed. During the experiment, the number of browsing history data is about one million, which is gotten from 945 students real web browsing behavior. About 84% students behavior can be classified eventually. This method gets good effect and improves the value of the web browsing history data and accuracy of crawling page information.
机译:为了提高Web浏览历史数据的价值并评估PEOPLES Web浏览行为,设计了一种基于TF-IDF和Naive Bayes浏览历史数据的方法,用于在互联网上对Peoples行为进行分类。在实验期间,浏览历史数据的数量约为一百万,从945名学生真实的Web浏览行为中得到了。大约84 %的学生行为最终可以分类。此方法效果良好,提高了Web浏览历史数据的价值和爬网信息的准确性。

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