A New Representation of WordNet® using Graph Databases by Khaled Nagi.
Abstract:
WordNet® is one of the most important resources in computation linguistics. The semantically related database of English terms is widely used in text analysis and retrieval domains, which constitute typical features, employed by social networks and other modern Web 2.0 applications. Under the hood, WordNet® can be seen as a sort of read-only social network relating its language terms. In our work, we implement a new storage technique for WordNet® based on graph databases. Graph databases are a major pillar of the NoSQL movement with lots of emerging products, such as Neo4j. In this paper, we present two Neo4j graph storage representations for the WordNet® dictionary. We analyze their performance and compare them to other traditional storage models. With this contribution, we also validate the applicability of modern graph databases in new areas beside the typical large-scale social networks with several hundreds of millions of nodes.
Finally, a paper that covers “moderate size databases!”
Think about the average graph database you see on this blog. Not really in the “moderate” range, even though a majority of users work in the moderate range.
Compare the number of Facebook size enterprises with the number of enterprises generally.
Not dissing super-sized graph databases or research on same. I enjoy both a lot.
But for your average customer, experience with “moderate size databases” may be more immediately relevant.
I first saw this in a tweet from Peter Neubauer.