Fuzzy Semantic Search Engine

Almost all the search engines that exist retrieve web pages by finding the exact keywords. The traditional keyword-based search engines suffer many problems, like synonyms and terms similar to keywords are not taken into account to search web pages, they treat all keywords as the same importance and cannot differentiate the importance of one keyword from that of another. Synonyms and terms similar to keywords are not taken into consideration to search web pages. Users may need to think of and input several similar keywords individually to complete a search. The restriction of exact keywords makes it inconvenient for users to search web pages. Many valuable web pages would be omitted if users did not search for several similar keywords individually. While users input several keywords to search web pages, different keywords may have different degrees of importance in their opinions. Traditional search engines treat all keywords as the same importance and cannot differentiate the importance of one keyword from that of another. The problem of information overload makes it difficult for users to find really useful information from a large amount of search results. Traditional search engines lack an applicable classification mechanism to reduce the search space and improve the search results. To alleviate the mentioned problems that the users face, in this paper we have proposed and applied the fuzzy logic theory and the semantic search techniques to develop a fuzzy semantic search engine.