Abstract

Blogging plays a major role in today's social networking. Large numbers of blogs are available in the web. This becomes a tedious task for the user and the blogger, to search for a technical blog from a list of randomly appearing blogs. Thus a method is required to rank the blogs for the user, according to the relevance of the query. The existing works focus either on the behaviour of the blogger or the linking of one blog with another blog. This paper introduces a novel method of ranking blogs based on the relevance of the content to the query. The semantics of the query is analysed to rank the blogs. The proposed method also uses concept-based profiling, to enable the user to retrieve personalised content for the query. The experimental analysis shows that the proposed personalised semantic blog ranking PSBR is efficient in ranking the technical blogs for the user.

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