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A Method of Behavior Evaluation Based on Web Browsing Information

机译: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:为了提高网页浏览历史数据的价值,评估人们的网页浏览行为,设计了一种基于TF-IDF和朴素贝叶斯的浏览历史数据的方法,该方法用于对互联网上人们的行为进行分类。在实验过程中,浏览历史数据的数量约为一百万,这是根据945名学生的实际Web浏览行为得出的。最终,大约有84%的学生行为可以分类。该方法效果良好,提高了网页浏览历史数据的价值和爬网信息的准确性。

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