Abstract
The blogosphere is a part of the World Wide Web, enhanced with several characteristics that differentiate blogs from traditional websites. The number of different authors, the multitude of user-provided tags, the inherent connectivity between blogs and bloggers, the high update rate, and the time information attached to each post are some of the features that can be exploited in various information retrieval tasks in the blogosphere. Traditional search engines perform poorly on blogs since they do not cover these aspects. In an attempt to exploit these features and assist any specialized blog search engine to provide a better ranking of blogs, we propose a rating mechanism, which capitalizes on the hyperlinks between blogs. The model assumes that the intention of a blog owner who creates a link to another blog is to provide a recommendation to the blog readers, and quantifies this intention in a score transferred to the blog being pointed. A set of implicit and explicit links between any two blogs, along with the links’ type and freshness, affect the exchanged score. The process is iterative and the overall ranking score for a blog is subject to its previous score and the weighted aggregation of all scores assigned by all other blogs.
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Louta, M., Varlamis, I. (2010). Blog Rating as an Iterative Collaborative Process. In: Wallace, M., Anagnostopoulos, I.E., Mylonas, P., Bielikova, M. (eds) Semantics in Adaptive and Personalized Services. Studies in Computational Intelligence, vol 279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11684-1_11
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DOI: https://doi.org/10.1007/978-3-642-11684-1_11
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