Implementing Triple Stores using NoSQL Databases
Knowledge bases empower various information retrieval systems nowadays. The usual implementation of them is through RDF based triple stores. The available toolkits that enable this are usually less mature in comparison with well established document oriented NoSQL databases. In this work we report on an alternative implementation of triple stores using NoSQL databases. In comparison with similar solutions in this regard, we decided to not use RDF at all, therefore no data or query mapping was needed. We propose the implementation of a vocabolary using a separate document collection. This would also facilitate the dynamic enlargement of it in automated fact extraction scenarios. Our results show that using a document oriented NoSQL database for storing and retrieving triples offers a considerable performance. The involved preprocessing needed because of the limitations of a non RDF based solution, did not affect this. The achieved performance was also higher in comparison with doing the same knowledge retrieval operations using a purposely built linked data toolkit.
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