چکیده (انگلیسی):

In today’s scenario, publishing the personal content and technical content has become very easy for the
publishers, because of the readily available prominent social media called blog. Content developers,
teachers, researchers post various articles relevant to their research or newly emerging topics. Blog content
in one blog source may resemble the semantics of blog from other source. Readers, who are fascinated in
reading the blog content, anticipate retrieving the blogs from different sources for their query. A large
number of posts are available in the web. Hence the blog reader’s task becomes very complex to search the
relevant content for their query. This study introduces a novel idea to collect the blog using unified
Semantic Blog Mining Framework (SBMF). SBMF collects blogs from different blog sources using the
ontology constructed for education domain. Blogs collected from different sources are collection which
contains relevant or irrelevant blogs. The new blog summarizer summarizes the blog content and ranks the
blogs according to the similarity of the blog with query given by the user. The proposed blog summarizer
check the similarity of each sentence in a blog, sort the order of sentence based on the similarity of the text
with query word and reduces the number of sentences. The experimental results shows that the proposed
unified SBMF and blog summarizer produces better relevant and summarized number of blogs compared to
various search engines. SBMF confirms the hundred percentage relevancy compared to other blog search
engines. Blog summarizer yields accurate summarization for the collected blogs.