Semantic Search Engine
Search engines are fundamental tools to find information from the Web, but the enormous amount of data stored over the internet has increased the difficulty in retrieving relevant results. In most cases, keyword-based search engines rely on the matching between the terms entered by the user and the terms contained in an index. This approach may arise several problems because the user and the index may not use the same term but, for example, a synonym or a spelling variation. Query expansion is a common approach that deals with these issues by reformulating the user query, adding new terms in order to improve information retrieval performances. In this project, we developed a web search engine that uses Linked Data in order to expand the user queries and to return more relevant results. Full description on GitHub.