On-Demand and Lightweight Knowledge Graph Generation -- a Demonstration with DBpedia
This addresses the issue of computational inefficiency and data staleness for users of knowledge graphs like DBpedia, though it appears incremental as it builds on existing systems.
The paper tackles the problem of large-scale knowledge graphs requiring extensive resources and having outdated information by presenting DBpedia on Demand, a system that serves DBpedia resources on demand without materializing the entire graph and offers limited querying functionality.
Modern large-scale knowledge graphs, such as DBpedia, are datasets which require large computational resources to serve and process. Moreover, they often have longer release cycles, which leads to outdated information in those graphs. In this paper, we present DBpedia on Demand -- a system which serves DBpedia resources on demand without the need to materialize and store the entire graph, and which even provides limited querying functionality.