Sentence examples for data-driven knowledge from inspiring English sources

This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna.

To identify learner's mental states, the ontology operates on the basis of the theoretical and data-driven knowledge of emotions.

Companies, like civilisations, advance by leaps and bounds when genius is let loose, not when genius is locked away and deemed too out of the mainstream of data-driven knowledge.

Furthermore, it combines several concepts of intelligent systems, including Machine Learning and Data Mining, with topics derived from expert systems, as user and data-driven knowledge, with meta-knowledge.

To this end, the proposed approach is evaluated on three diverse ASR tasks: continuous phone recognition, connected digit recognition, and large vocabulary continuous speech recognition, but the data-driven knowledge module is trained with a single corpus and used in all three evaluation tasks without further training.

Our work illustrates the feasibility of contact measures through RFID devices in hospital settings, aimed at providing data-driven knowledge to inform models and prevention strategies.

He will play down the risk of the "productivity puzzle" – the weak growth in output-per-hour achieved since the crisis – saying: "In our data-driven, knowledge-based economy, where services play a key role, it's less and less just about the quantity of widgets coming off production lines and more and more about the quality of customer interaction".

Detailed provenance information and full traceability of all data and analytical components becomes even more critical in an emerging big-data-driven knowledge reengineering scenario (Hoekstra, 2011; Robbins and Chiesa, 2011).

While it is common to construct a gold standard from a synthetic or a simulated network, we aim to assess the predictive power of two types of models (i.e., data-driven versus knowledge-driven) in the presence of future knowledge.

Validation of the transferred annotations showed their high reliability, which makes them suitable to be used for data-driven biomedical knowledge discoveries.

To overcome the critical challenges, some unique benefits from data-driven and knowledge elicitation techniques are availed in this paper and a new approach to construct hierarchical multistage BIN and quantify the inference nodes is proposed.