以前的算法是根据点击数目来排行，有很多不足的地方，比如没有考虑时间因素，没有考虑用户对其的推荐等因素，我打算以文章浏览次数，评论次数，引用次数以及文章的日期来生成。把用户的评论数目作为推荐次数，文章的发表日期到今天的时间做为时间因素。

　　1条评论和100次浏览有相同积分。

　　1条Traceback等于2条评论的积分。评论和引用的增长是线性的。

　　浏览次数增大，取得的积分以开平方根的方式增长，即数字越大，变化越小。

　　文章的日期做为负积分，以指数方式增长，越老的文章，会变为越来越大的负数积分。

-Date to generate the previous algorithm is based on the number of hits to ranking, there are many flaws, such as not considering the time factor, without considering other factors as users of its recommended, I intend to article Views, review times cited article . Number of user reviews as recommended number of times, the article' s publication date to today as the time factor. 1 comments viewed 100 times the same integral. A Traceback integral equals 2 Comments. Comments and trackbacks growth is linear. Views increases made integral to the square root of the way of growth, that is, the larger the number, the smaller the change. The date of the article as negative points, an exponential growth in the older articles will become increasingly negative integral.