Sentence examples for categorization of texts from inspiring English sources

The fifth section turns to an intellectual divergence between generalist and technical specialist knowledge through the categorization of texts in a chapter of the dynastic history of the Han dynasty (Han shu).

Digital technologies first brought a categorization of texts as printed or digital; a more recent distinction considers whether texts are static (printed and similar digital counterparts such as in pdf or epub formats), or dynamic (hypertext or digital texts) (OECD, 2009).

To solve the problem of effective of categorization of text data in taxation system, the paper analyses the text data and the size calculation of key issues first, then designs text categorization based on rough set model.

An initial code manual was developed based on the research questions and this provided a framework for the initial categorization of text.

We believe that the categorization of text along the multiple suggested dimensions, which characterize important aspects of scientific contents, can lead to more accurate extraction and retrieval of information from a large volume of publications.

It provides Gene Ontology (GO) and Medline Subject Headings (MeSH) categorization of text passages, the retrieval of relevant publications from public scientific literature repositories, and the identification of missing or unused references.

Specifically, this study used free coding, iterative categorization of text fragments, and reciprocal translational analysis from meta-ethnography, integrating these techniques with grounded theory's inductive approach and constant comparison method [ 28, 29].

This scheme allows the categorization of text along multiple important dimensions, supporting the identification of information that has been recently pointed out by biologists and biological database curators as highly desirable, including: experimental evidence, indirect evidence, description of methods, positive versus negative statements and others.

First, Legalists were not a self-aware and organized intellectual current; rather the name was coined as a post-factum categorization of certain thinkers and texts, and its primary function before the twentieth century was that of a bibliographical category in imperial libraries.

The description is of feature extraction in text categorization of several typical application of CNN model.

Consequently, spam filtering poses a special problem in text categorization, of which the defining characteristic is that filters face an active adversary, which constantly attempts to evade filtering.