Sentence examples for a text generation from inspiring English sources

A text generation model is proposed based on keyword generation model and sentence generation model.

#1, use a text generation site.

These models represent the best tradeoff between computational efficiency and output accuracy that we could obtain over a large number of experiments in text generation.

A remarkable example is the Yule-Simon model for text generation [41] that was later rediscovered in the context of citation analysis [42], and has recently found broad popularity in the complex networks literature [43].

From a broader perspective, it seems natural that models of text generation should be based on similar cognitive mechanisms as models of human text processing since text production is a translation of semantic concepts in the brain into external lexical representations.

transcription; familiarisation with the text; generation of initial codes; searching for themes; reviewing themes; and generating thematic maps.

The stages include: transcription; familiarisation with the text; generation of initial codes; searching for themes; reviewing themes; and generating thematic maps.

This paper presented a novel application of factored language models (FLMs) in the field of text generation, in which FLMs are intended to overcome data sparseness, an issue that is particularly prevalent in morphologically-rich language processing.

It can also provide functions such as an internist model evaluation using perplexity, N-best rescoring and model-based text generation.

The system includes concept expansion module, text generation module and content replacement module.

The system includes text generation module, synonym substitution module and simile expression module.