Sentence examples for use of external knowledge from inspiring English sources

Existing chunking systems make use of external knowledge, e.g. grammar parsers, or integrate multiple learners to achieve higher performance.

The use of external knowledge for innovation (i.e., inbound or outside-in open innovation) has received substantial attention in the innovation literature.

Many studies have presented the use of external knowledge, resources, and human power as means of utilizing SMEs' strengths and as factors that offset their insufficient capabilities in internal R&D [11 14].

In addition to the text representation model, text semantics can also be incorporated to text mining process through the use of external knowledge sources, like semantic networks and ontologies, as discussed in the "External knowledge sources" section.

Wimalasuriya and Dou [17], Bharathi and Venkatesan [18], and Reshadat and Feizi-Derakhshi [19] consider the use of external knowledge sources (e.g., ontology or thesaurus) in the text mining process, each one dealing with a specific task.

Drawing on the human capital, learning and creativity literatures, we theorize that knowledge diversity of the firm's employees is positively associated with employees' ability to identify and absorb external knowledge, which aggregates to increased firm-level openness that is, firms' use of external knowledge in their pursuit of innovation.

Through external networking with larger companies, other SMEs, universities, and public or private research institutes, manufacturing SMEs can make use of these sources of external knowledge and technology for product innovation or can engage customers in the process of product innovation through the use of their customers' knowledge.

We propose a framework where GI networks are learned from experimental data using Bayesian networks (BNs) and the incorporation of external knowledge is also done via a BN that we call Bayesian Network Prior BNPP).

Logistic regression using BMA was applied to estimate the contribution of each type of external knowledge in the prediction of regulatory relationships.

It required a deep knowledge of chemistry, supported with consultation of external knowledge sources in case of doubt.

The library supports the loading and integration of external knowledge bases, as well as references to external entities.