Blogs Search Engine Using RSS Syndication and Fuzzy Parameters

The rapid development of the internet eventually increases the number of internet users triggering the need for an intelligent search engine that is able to minimize the search on world wide web (WWW) and find relevant information as requested. To overcome the issue of finding relevant information as well as minimizing the search on WWW, this paper proposes a search engine that is specifically designed and built using RSS syndication and fuzzy Parameters to search for information contained in blogs. The blogs search engine consists of three main phases: 1) crawling using RSS feeds algorithm; 2) indexing weblogs algorithm; and 3) searching technique using fuzzy logic. In RSS crawling process, the RSS feeds need to be gathered to extract useful information such as title, links, time published, and description. Next, indexing weblogs uses the links to retrieve the blog sites for text processing and for constructing the indexing database. In order to retrieve such information requested or queried by any user, an interface is provided to enable the blog search based on keyword with associated degree of importance. The density of keyword is then computed from the indexing database. The rank of the pages is computed by using fuzzy weighted average. The experiment resulted in mean average precision of 81.7% of total system performance. Keywords—Rss feeds, blog ssearch engine, fuzzy weighted average, keyword density.