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Semantics based Search Engine

Semantics based Search Engine focuses on the semantics of the language. It uses this information to perform a keyword(s) based search. Instead of just treating the query as a set of keywords, the engine tries to create a coherent meaning out of the user’s search query. It tries to understand the relationship among various keywords present in the user’s query and returns a set of documents which are then ranked according to their relevance to the user’s query. It uses pronomial corelation (apart from tf-idf and citation) present in the text to form an index of the documents.

The information contained in the semantics of the language conveys a deeper meaning of what the user is actually looking for. Performing a keyword based search often returns a set of documents which are irrelevant. The engine proposed above focuses on providing only the relevant results instead of providing the results containing the keywords in the user’s search query. To do so, the engine has a Natural Language based parser querying an index which in turn is built by analysing the content present in the documents . Focusing on content along with citation augments the relevancy of the documents.

For instance, a search for the phrase National Treasure will return a set of pages containing the information about the movie National Treasure rather than the pages containing information about, let’s say, a British National who found the hidden Treasure. The latter may have been cited at a lot of places but it is not at all relevant to the user’s search query.

 

 

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