Sentence examples for knowledge in text from inspiring English sources

"Just having knowledge in text form and online, divorced from those connections, is a bit strange," he said.

While large-scale taxonomies ontologies exist both for the general [6, 7] and the medical domain (e.g. UMLS 1., their sheer size impose a high burden on anyone that tries to make knowledge in text explicit: annotators would have to learn these ontologies or at least relevant parts of these ontologies in order to properly carry out their task.

First of all, headache specialists translated diagnostic knowledge in text-based guideline (ICHD) into a thought process of headache diagnosis.

The primary goal of text mining is to retrieve knowledge hidden in text and to present the distilled knowledge such as associations, patterns to users in a concise form [ 11].

Ontologies can be used as background knowledge in a text mining process, and the text mining techniques can be used to generate and update ontologies.

Biomedical named entity recognition (BNER) is a critical component in automated systems that mine biomedical knowledge in free text.

Chemists can then search for similar structures or substructures, and the knowledge in the text can be combined with the knowledge from chemical databases.

This enables a chemist to search for similar structures or substructures and combine the knowledge in the text with knowledge from databases or to integrate other tools handling chemical information (e.g. solubility or mass calculation).

19 20 22 NLP has been developing for over 30 years, but the difficulties in developing a system that can recognise syntax, semantics and domain knowledge in free text are many and complex.

It is promising to extract specific transporter and substrate information from the wealth of biomedical knowledge in free text due to the increasing number of stored literature in databases such as PubMed and UniProt.

Biomedical named entity recognition (BNER), which extracts important named entities such as genes and proteins, is a challenging task in automated systems that mine knowledge in biomedical texts.