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Text normalization is the process of transforming text into a single canonical form that it might not have had before. Normalizing text before storing or processing it allows for separation of concerns, since input is guaranteed to be consistent before operations are performed on it. Text normalization requires being aware of what type of text ...
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
Coherence in linguistics is what makes a text semantically meaningful. It is especially dealt with in text linguistics.Coherence is achieved through syntactic features such as the use of deictic, anaphoric and cataphoric elements or a logical tense structure, and semantic features such as presuppositions and implications connected to general world knowledge.
The data obtained by this form is regarded as a static representation of handwriting. Offline handwriting recognition is comparatively difficult, as different people have different handwriting styles. And, as of today, OCR engines are primarily focused on machine printed text and ICR for hand "printed" (written in capital letters) text.
Formatted text has its genesis in the pre-computer use of underscoring to embolden passages in typewritten manuscripts.In the first interactive systems of early computer technology, underlining was not possible, and users made up for this lack (and the lack of formatting in ASCII) by using certain symbols as substitutes.
Complex text layout (CTL) or complex text rendering is the typesetting of writing systems in which the shape or positioning of a grapheme depends on its relation to other graphemes. The term is used in the field of software internationalization , where each grapheme is a character .