Abstract
Knowledge bases are playing an increasingly important role in many real-world applications.
However, most of these knowledge bases tend to be outdated, which limits the utility of these knowledge bases.
In this paper, we investigate how to keep the freshness of the knowledge base by synchronizing it with its data source (usually encyclopedia websites).
A direct solution is revisiting the whole encyclopedia periodically and rerun the entire pipeline of the construction of knowledge base like most existing methods.
However, this solution is wasteful and incurs massive overload of the network, which limits the update frequency and leads to knowledge obsolescence.
To overcome the weakness, we propose a set of synchronization principles upon which we build an Update System for knowledge Base (USB) with an update frequency predictor of entities as the core component.
We also design a set of effective features and realize the predictor.
We conduct extensive experiments to justify the effectiveness of the proposed system, model, as well as the underlying principles.
Finally, we deploy USB on a Chinese knowledge base to improve its freshness.
Keywords
- Multidisciplinary Topics and Applications: Real-Time Systems
- Natural Language Processing: Information Extraction
- Multidisciplinary Topics and Applications: Multidisciplinary Topics and Applications
