Sentence examples for readable knowledge from inspiring English sources

In this paper, to obtain readable knowledge from data, we propose a new neuro-fuzzy model and its learning algorithm that works in a parameter space with reduced dimensionality.

The recent developments in crowdsourcing technologies have opened new promising opportunities to overcome this problem by exploiting large amounts of machine readable knowledge to perform tasks requiring human intelligence.

Hierarchies were assembled leveraging as much as possible machine-readable knowledge from existing resources.

Future research will focus on a representation that closes the gap between machine-readable and human-readable knowledge representations.

Ontologies and attribute-based models encode explicit human-readable knowledge, while word vector models offer a good computation framework based on vector spaces.

The study of disease-phenotype relationships has been hampered by the scarcity of suitable large-scale, machine-readable knowledge bases.

The goal of this work was to create and analyze an ensemble database that represents the superposition of machine-readable knowledge on the topologies of inflammatory networks in humans as a prelude to more detailed network analysis and mathematical modeling.

Due to lack of agreed-upon consensus in the community and the relative sparsity of machine-readable anatomical knowledge across several of the needed dimensions, the NeuroMorpho.Org brain region hierarchies were assembled from a number of external references.

The overall picture shows that not only are semi-structured resources enabling a renaissance of knowledge-rich AI techniques, but also that significant advances in high-end applications that require deep understanding capabilities can be achieved by synergistically exploiting large amounts of machine-readable structured knowledge in combination with sound statistical AI and NLP techniques.

The method also enables the definition of prediction intervals for the fuzzy rules that constitute the rule base of the neuro-fuzzy network, resulting in a more readable and robust knowledge base.

The resulting information is instantiated as a machine-readable electronic relational knowledge base that is publicly and freely available, facilitating web accessibility and computational analytics.