Ontology based Domain Specific Web Search Engine - Agrawal, Daksh; Sanghani, Hirali; Jadhav, Sonali; Shinde, Supriya (International Journal of Computer Sciences and Engineering, 2015)
Most of the existing search engines retrieve web pages by means of finding exact keywords. Traditional keyword-based search engines suffer several problems. First, synonyms and terms similar to keywords are not taken into consideration to search web pages. Users may need to input several similar keywords individually to complete a search [1]. Second, traditional search engines treat all the keywords as the same importance and cannot differentiate the importance of one keyword from that of another. Third, traditional search engines lack an applicable classification mechanism to reduce the search space and improve the search results. In this system, we develop a Semantic Search Engine. First, a fuzzy ontology is constructed by using fuzzy logic to capture the similarities of terms in the ontology, which offering appropriate semantic distances between terms to accomplish the semantic search of keywords. Second, users can check or uncheck the pages results based on their needs to show or hide it next time they search it. The totally satisfactory degree of keyword scam be aggregated based on their degrees of importance and degrees of satisfaction [2] [3]. Third, the domain classification of web pages offers users to select the appropriate domain for searching web pages, which excludes web pages in the inappropriate domains to reduce the search space and to improve the search results.