Blogs are one of the main user generated content on the web. So, it is necessary to present retrieval algorithms to the meet information need of weblog users. The goal of blog feed search is to rank blogs regarding their recurrent relevance to the topic of the query.
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Blogs are one of the main user generated content on the web. So, it is necessary to present retrieval algorithms to the meet information need of weblog users. The goal of blog feed search is to rank blogs regarding their recurrent relevance to the topic of the query.
In this paper, the state-of-the-art blog retrieval methods are surveyed and then they are evaluated and compared in Persian blogosphere. Also, one of the best retrieval models is optimized by using data fusion methods. Evaluation of the proposed algorithm is carried out based on a standard Persian weblogs dataset with 45 diverse queries. Our comparisons show considerable improvement over existing blog retrieval algorithms.
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