Today, most Web pages are being created in the blog space or evolving into the blog space. A major problem is that a blog entry (blog page) includes non-traditional features of Web pages. Those are trackback links, bloggers' authority, tags, and userspsila responses. Thus, the traditional rank algorithms are not proper to evaluate blog entries because those algorithms do not consider the blog specific features. In this paper, we propose a new algorithm called "trackback-rank" that ranks blog entries by calculating the reputation scores of bloggers, trackback scores, and comment scores based on the features of the blog entries. We apply this algorithm to searching for information related to the userspsila queries in the blog space. The experiment shows that our algorithm finds the much more relevant information than the traditional ranking algorithms.
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