Sentence examples for steps of text from inspiring English sources

Text semantics can be considered in the three main steps of text mining process: pre-processing, pattern extraction and post-processing.

Whether previous knowledge is considered in the steps of text representation and analysis makes a major difference: A pure machine learning approach relies on probabilistic models, whereas a knowledge-based approach involves "existing knowledge resources" such as pre-defined ontologies or training data [74].

This screenshot shows the individual editing steps of text input, adding lines and setting the background color for a text frame.

The step of text representation might be supported by text parsers, e.g., the Stanford Parser [121] or the TreeTagger [122], which provide information on syntax.

Technically, the quantization of similar local descriptors into a single patch can be thought of as being similar to the stemming preprocessing step of text documents, which consists of replacing all words by their stem.

As for the application of FLA in classroom instruction, the chapter offers a summary of the basic steps of infusing text analysis and discussion into content area instruction.

The consolidated list of all tags is used, which may be assigned to tokens at different steps of the text preprocessing stage, as specified in the Table 4.

The specifications stated in the problem identification step will guide the next steps of the text mining process, which can be executed in cycles of data preparation (pre-processing step), knowledge discovery (pattern extraction step), and knowledge evaluation (post-processing step).

Following the generic steps of the text mining, the main results of the data analysis procedure are reported in this section showing average patterns in terms of main topics and network links that could be identified in the 16 municipal MCAPs of regional centers in Lower Saxony.

To conclude, we would like to reiterate that stable FS enables an in-depth analysis of discriminative features and provides insight in the different steps of biomedical text mining.

Gene named entity recognition and normalization are the important preprimary steps of biomedical text mining and have been studied for many years, and evaluated in many benchmark datasets, such as JNLPBA (24) and BioCreative challenges (7, 25, 26).