Semantic Search Engine

Background/Objectives: Traditional keyword-based search engines retrieve web pages by matching the exact tokens or words in the user query with the tokens or words in the web documents. This approach has many drawbacks. Synonyms or terms similar to tokens or words in the user query are not taken into consideration to search web pages. The keyword based search engine gives equal importance to all keywords whereas when user will enter query, he may have different levels of importance for different keywords in his opinion. To get the correct relevant result, users may need to enter several synonyms on his own to get the desired information which may otherwise result into the omission of many valuable web pages. Another problem is of information overloading. The traditional keyword based search engines make it very tedious for end user to locate the really useful information from a huge list of search results. Existing web is dominated by keyword based Search Engines which does not provide an appropriate mechanism to classify and locate the relevant search results. This leads to wastage of precious time of end user if he does not know the key terms which are utilized to index preferred correct pages. To resolve the above mentioned issues that the users face, in this paper we have proposed search techniques to develop Ontology based semantic search engine. Methods/Statistical Analysis: Ontology based Semantic Search Engine for the tourism domain is developed that understands the meaning of the user query and relatively provides the direct, precise and relevant result. Not only the user entered keyword based pages would be returned but also the pages that are appropriate enough with the meaning of the user entered keyword were also be returned by using the Ontological synonym dataset developed by using WordNet. Findings: Firstly, the Ontology Synonym set is constructed using WordNet and then the ontology synonym set parser is used to map the user defined query with the query prototype. By comparing the Query Similarity for every prototype, the service/sub domain with maximum query similarity is identified and the respective service is invoked. Also if the similarity is 100% the extra keywords are also considered to provide the relevant and precise results to the end user. Meta-processor will provide meta information about the URL. Application/ Improvements: The proposed Ontology based semantic search engine in tourism domain is an enhanced model. This model can be used by search engines, tourism industry professional and customers in getting better results of the searches undertaken. After testing in real world, the improvements can be worked out.