A Semantic Search Engine in the Cloud

Due to the ease of data production within the Internet era, knowledge workers are increasingly overwhelmed by information from multiple information sources and yet still find it hard to navigate and search for accessing the specific information required for the task at hand. This implies that knowledge worker productivity is reduced and that organizations may be making decisions on the basis of incomplete knowledge. Most search engines in use today strongly rely on keywords matching and on the ability of the user in the query expression. This leads to the retrieval of a large amount of irrelevant information with a direct impact on the user that spends a lot of time in browsing the results and/or to construct more complex queries to refine the search output. To overcome this limitation semantic-based solution are increasingly adopted. In this work we propose a general architecture that implements a semantic search engine in the cloud that exploits semantic technologies to retrieve and present the right information to the user. Our search engine is aimed at providing support in the task of document composition, suggesting to the user the adequate section that could be inserted within a document.