Information enrichment using TaToo's semantic framework
Abstract
The Internet is growing in a non-coordinated manner, where different groups continuously publish and update information, adopting a variety of standards, according to the specific domain of interest: from agriculture to ecology, from groundwater to climate change. This unconstrained and unregulated growth has proven to be very successful, as more information is made available, even more is being added, in a virtuous cycle of information accrual. At the same time, modern search engines make looking for information rather easy, with their overall performance being more than satisfactory for most users. Yet, searching and discovering information requires a good deal of expertise and pre-existing knowledge. That may not be a problem when a user searches for common assets using a generic-purpose search engine. But what happens when the user is trying to gather scientific information across boundaries (e.g. cross different disciplines, cross environmental domains, etc)? This asks for new approaches, methods and tools to close the discovery gap of information resources satisfying your specific request. This is exactly the challenge the TaToo project is heading to.
Download full text in pdf format
Published as:
G. Schimak,
A. E. Rizzoli,
G. Avellino,
T. Pariente Lobo,
J. Fuentes,
I. N. Athanasiadis,
Information enrichment using TaToo's semantic framework,
4rd Intl Conf on Metadata and Semantics Research (MTSR 2010), CCIS,
2010, Springer, doi:10.1007/978-3-642-16552-8_15.
You might also enjoy (View all publications)
- Domain adaptation with transfer learning for pasture digital twins
- Causality and Explainability for Trustworthy Integrated Pest Management
- Breeding Programs Optimization with Reinforcement Learning