Sentence examples for segmentation of text from inspiring English sources

The database is also accompanied with tools that allow segmentation of text images into lines and paragraphs.

As a result, accurate segmentation of text regions from non-text regions (graphics/images) in mixed and complex documents is a fairly difficult problem.

Much work has been done on the segmentation of texts in the general or biomedical domains [ 18– 22].

Document image-level operations include: removal of pre-printed matter, segmentation of handwritten text lines and extraction of words.

A specific type of deduplication involves merging records from bibliographic databases that refer to the same article or book (this may or may not involve segmentation of free text into structured record fields) (3, 12).

The participants in the dialogues must therefore be different, and de Laat's segmentation of the texts is "unstable".

More specifically, linguistic analyses generally consist of the following processes: - Segmentation of free-text data into lexical units (single words, compound words).

Therefore, the next step in the text classification process includes segmentation of the used text corpora into the small segments (paragraphs) with at least 300 words.

More recently, the segmentation of classical Chinese text has been considered by Luo et al. 羅鳳珠等 (2013).

In-line annotations include the segmentation of document's text into passages and optionally sentences.

To explore themes and interactions among these themes, we followed a systematic data reduction process that consisted of the following steps: reading of transcripts, document summaries and observation notes, segmentation of sentences and phrases, codification of text segments, generation of themes and categories, and identification of relationships [ 52].