Palazzo Matrix Model: An approach to simulate the efficient semantic results in search engines

Searching of data over the web by the users is increasing day to day. Many search engines are feasible in the market to provide services to the users to achieve relevant data and knowledge. But, most of the time the search engines fail to provide the exact information what the users really seek, i.e., losing the relevancy of the retrieved documents for the queries. In recent years, semantic search engines have arrived with considerable research efforts which aim to improve the retrieval process and traditional information search. This paper presents different models to calculate the relevancy of the document retrieved for the given query and also introduce a novel approach Palazzo Matrix Approach to retrieve the most relevant documents that use lemmatization and stemming processes to match terms which are in the given query. Based on this approach, various experiments were conducted to evaluate the effectiveness of search engines using different measures such as precision and recall on multiple as well as single word search queries given by the users to either semantic or keyword based search engines.