Caseng: Arabic semantic search engine

Accurate information availability is a key factor for knowledge acquisition without going into extraneous information. Understanding searcher intent and the contextual meaning of terms as they appear in the searchable dataspace is a challenge that has been addressed and handled by many semantic search engines. As meaning encoded separately from data in semantic technology, adding, changing and implementing new relationships can be done easily. The evolution of semantic search added a new dimension of challenge due to a lack in support of the Arabic language. In this paper, we figure out the problem and implement a Semantic Search Engine (CASEng) for College of Applied Sciences, Oman. CASEng supports both Arabic and English search. It uses a Resource Description Framework (RDF) data and Lucene for indexing and searching to move from keyword-based search via Google and other engines to semantics-based search. The experiments show that both the spell-checker and the search engine perform well with a set of test queries.