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Degree of user attention to a webpage based on Baidu Index: an alternative to page view

机译:用户对基于百度索引的网页的关注度:一种页面浏览的替代方法

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Due to mass information on the Internet, efficient information retrieval has become the topic of interest for both academia and industry. In order to improve the accuracy of search engines' ranking algorithm, we propose an algorithm for determining the theoretical degree of user attention to a webpage (TDUAW). News webpages were selected from the Chinese online forums as the object of our research. We designed a content-oriented algorithm for TDUAWs through such steps as extracting web content, identifying the feature vector of a webpage and calculating the degree of user attention based on Baidu Index. Experiment and regression analyses were conducted on 150 webpages. The results indicate that the optimal number of feature words is three and the correlation coefficient between the theoretical degree of user attention and the actual degree of user attention (net page view) is over 0.8, which proves the validity of our method. So, the theoretical degree of user attention can serve as an alternative to the page view in the case when page view is unavailable.
机译:由于Internet上的海量信息,有效的信息检索已成为学术界和工业界关注的话题。为了提高搜索引擎排名算法的准确性,我们提出了一种用于确定用户对网页的理论关注度的算法(TDUAW)。从中国在线论坛中选择新闻网页作为我们研究的对象。我们通过提取网页内容,识别网页的特征向量以及基于百度索引计算用户的关注度等步骤设计了针对TDUAW的面向内容的算法。在150个网页上进行了实验和回归分析。结果表明,特征词的最佳数目为3,理论上的用户关注度与实际用户关注度(网页浏览量)之间的相关系数大于0.8,证明了该方法的有效性。因此,在页面视图不可用的情况下,理论上的用户关注度可以替代页面视图。

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